From 483b09b3c9f066dfdca7ce4ba96bd184051f1af7 Mon Sep 17 00:00:00 2001 From: Christine Straub Date: Thu, 24 Aug 2023 17:46:19 -0700 Subject: [PATCH] Feat/1136 elements ordering for pdf (#1161) ### Summary Address [#1136](https://github.com/Unstructured-IO/unstructured/issues/1136) for `hi_res` and `fast` strategies. The `ocr_only` strategy does not include coordinates. - add functionality to switch sort mode between the current `basic` sorting and the new `xy-cut` sorting for `hi_res` and `fast` strategies - add the script to evaluate the `xy-cut` sorting approach - add jupyter notebook to provide evaluation and visualization for the `xy-cut` sorting approach ### Evaluation ``` export PYTHONPATH=.:$PYTHONPATH && python examples/custom-layout-order/evaluate_xy_cut_sorting.py ``` Here, the file should be under the project root directory. For example, ``` export PYTHONPATH=.:$PYTHONPATH && python examples/custom-layout-order/evaluate_xy_cut_sorting.py example-docs/multi-column-2p.pdf fast ``` --- .gitignore | 5 +- CHANGELOG.md | 2 + example-docs/multi-column-2p.pdf | Bin 0 -> 194794 bytes example-docs/multi-column.pdf | Bin 0 -> 383508 bytes examples/custom-layout-order/README.md | 18 + .../evaluate_xy_cut_sorting.py | 155 +++++ test_unstructured/file_utils/test_filetype.py | 40 -- .../partition/pdf-image/test_pdf.py | 10 +- test_unstructured/partition/test_common.py | 44 +- .../azure/IRS-form-1987.pdf.json | 284 ++++---- .../azure/IRS-form-1987.png.json | 154 ++-- .../biomed-api/65/11/main.PMC6312790.pdf.json | 296 ++++---- .../biomed-api/75/29/main.PMC6312793.pdf.json | 216 +++--- .../07/07/sbaa031.073.PMC7234218.pdf.json | 38 +- .../layout-parser-paper.pdf.json | 342 ++++----- .../biomed-api/65/11/main.PMC6312790.pdf.json | 314 ++++----- .../biomed-api/75/29/main.PMC6312793.pdf.json | 170 ++--- .../07/07/sbaa031.073.PMC7234218.pdf.json | 20 +- .../2023-Jan-economic-outlook.pdf.json | 450 ++++++------ .../small-pdf-set/Silent-Giant-(1).pdf.json | 362 +++++----- .../recalibrating-risk-report.pdf.json | 272 ++++---- .../2023-Jan-economic-outlook.pdf.json | 656 +++++++++--------- .../small-pdf-set/Silent-Giant-(1).pdf.json | 276 ++++---- .../recalibrating-risk-report.pdf.json | 204 +++--- unstructured/file_utils/filetype.py | 107 +-- unstructured/partition/common.py | 99 ++- unstructured/partition/html.py | 3 +- unstructured/partition/pdf.py | 26 +- unstructured/partition/utils/__init__.py | 0 unstructured/partition/utils/constants.py | 2 + unstructured/partition/utils/sorting.py | 60 ++ unstructured/partition/utils/xycut.py | 255 +++++++ 32 files changed, 2688 insertions(+), 2192 deletions(-) create mode 100644 example-docs/multi-column-2p.pdf create mode 100644 example-docs/multi-column.pdf create mode 100644 examples/custom-layout-order/README.md create mode 100644 examples/custom-layout-order/evaluate_xy_cut_sorting.py create mode 100644 unstructured/partition/utils/__init__.py create mode 100644 unstructured/partition/utils/constants.py create mode 100644 unstructured/partition/utils/sorting.py create mode 100644 unstructured/partition/utils/xycut.py diff --git a/.gitignore b/.gitignore index 873213e8c9..abebba9478 100644 --- a/.gitignore +++ b/.gitignore @@ -187,4 +187,7 @@ tags # Ruff cache .ruff_cache/ -unstructured-inference/ \ No newline at end of file +unstructured-inference/ + +example-docs/*_images +examples/**/output/ \ No newline at end of file diff --git a/CHANGELOG.md b/CHANGELOG.md index 2b591bd606..1c75cb3b25 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,8 @@ ### Enhancements * Add threaded Slack conversations into Slack connector output +* Add functionality to sort elements using `xy-cut` sorting approach in `partition_pdf` for `hi_res` and `fast` strategies + ### Features ### Fixes diff --git 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zIAL~chBP-eq7BshAZ|m^W>n)qZBf(Mq13?j91-}Wmg8ZYU^vS9`fTwXC46tXdahD@k#}7d^9M8o`eq9!=sF$}Ui19TZpuTeQ#{{;x#&Oadea4W> z!ye^VwcdzY3$m3kg{fmUeVU_Tu&hpoAkEJuhN`|kf386s49BBmt5xgaSb+E(t@}r) z+nTPSjd150r1?4Lh_qgBP*_KIC+N)_>bb3~TCG1&69@jV)s@EH*ruZ!{ z%fcNXbe3sYT>CTODJr}=ALvr+mZ(o*gbRKHrjC$pWg7W(QM=3sJ#~5pXjqL`98S}6 zS(Xz`Gnvd`kAqSbk_AS_aSR*p8ptpyGo`Ze!^N}5P+W&coJv-y;1l=bo;nih9vLy{i{)8WQ8LpZ40 zz^=vNE^e-?{$X^paP*lIbw9u8@Z2~UuxkSzsoobLSM~l2R(ak`Vs~91T6rhy5+JnR z8&RKPyj8(KENk5tJQvjTYJ?c?))6PJZoHUJI{3joJ3SocdhU#r_zP}dMT&Ck5^J9t zpV3M=ISO2Jas``*mm#nsbG#lBaXyao( +``` +Here, the file should be under the project root directory. For example, +``` +export PYTHONPATH=.:$PYTHONPATH && python examples/custom-layout-order/evaluate_xy_cut_sorting.py example-docs/multi-column-2p.pdf fast +``` + +### Running jupyter notebook +The Google Colab version of the notebook can be found here: `/evaluate_xy_cut_sorting.ipynb` diff --git a/examples/custom-layout-order/evaluate_xy_cut_sorting.py b/examples/custom-layout-order/evaluate_xy_cut_sorting.py new file mode 100644 index 0000000000..8eb3f95d12 --- /dev/null +++ b/examples/custom-layout-order/evaluate_xy_cut_sorting.py @@ -0,0 +1,155 @@ +import os +import sys + +import cv2 +import matplotlib.pyplot as plt +import numpy as np +import pdf2image + +from unstructured.documents.elements import PageBreak +from unstructured.partition.pdf import partition_pdf +from unstructured.partition.utils.constants import SORT_MODE_BASIC, SORT_MODE_XY_CUT +from unstructured.partition.utils.xycut import ( + bbox2points, + recursive_xy_cut, + vis_polygons_with_index, +) + + +def show_plot(image, desired_width=None): + image_height, image_width, _ = image.shape + if desired_width: + # Calculate the desired height based on the original aspect ratio + aspect_ratio = image_width / image_height + desired_height = desired_width / aspect_ratio + + # Create a figure with the desired size and aspect ratio + fig, ax = plt.subplots(figsize=(desired_width, desired_height)) + else: + # Create figure and axes + fig, ax = plt.subplots() + # Display the image + ax.imshow(image) + plt.show() + + +def extract_element_coordinates(elements): + elements_coordinates = [] + page_elements_coordinates = [] + + for el in elements: + if isinstance(el, PageBreak): + if page_elements_coordinates: + elements_coordinates.append(page_elements_coordinates) + page_elements_coordinates = [] + else: + page_elements_coordinates.append(el.metadata.coordinates) + + if page_elements_coordinates: + elements_coordinates.append(page_elements_coordinates) + + return elements_coordinates + + +def convert_coordinates_to_boxes(coordinates, image): + boxes = [] + + for coordinate in coordinates: + points = coordinate.points + _left, _top = points[0] + _right, _bottom = points[2] + w = coordinate.system.width + h = coordinate.system.height + image_height, image_width, _ = image.shape + left = _left * image_width / w + right = _right * image_width / w + top = _top * image_height / h + bottom = _bottom * image_height / h + boxes.append([int(left), int(top), int(right), int(bottom)]) + + return boxes + + +def order_boxes(boxes): + res = [] + recursive_xy_cut(np.asarray(boxes).astype(int), np.arange(len(boxes)), res) + np_array_boxes = np.array(boxes) + ordered_boxes = np_array_boxes[np.array(res)].tolist() + return ordered_boxes + + +def draw_boxes(image, boxes, output_dir, base_name, page_num, output_type, label): + annotated_image = vis_polygons_with_index(image, [bbox2points(it) for it in boxes]) + + if output_type in ["plot", "all"]: + print(f"{label} elements - Page: {page_num}") + show_plot(annotated_image, desired_width=20) + + if output_type in ["image", "all"]: + output_image_path = os.path.join(output_dir, f"{base_name}_{page_num}_{label}.jpg") + cv2.imwrite(output_image_path, annotated_image) + + +def draw_elements(elements, images, output_type, output_dir, base_name, label): + elements_coordinates = extract_element_coordinates(elements) + + assert len(images) == len(elements_coordinates) + for idx, (img, coords_per_page) in enumerate(zip(images, elements_coordinates)): + image = np.array(img) + boxes = convert_coordinates_to_boxes(coords_per_page, image) + draw_boxes(image, boxes, output_dir, base_name, idx + 1, output_type, label) + + +def run_partition_pdf( + pdf_path, + strategy, + images, + output_type="plot", + output_root_dir="", +): + print(f">>> Starting run_partition_pdf - f_path: {pdf_path} - strategy: {strategy}") + f_base_name = os.path.splitext(os.path.basename(pdf_path))[0] + + output_dir = os.path.join(output_root_dir, strategy, f_base_name) + os.makedirs(output_dir, exist_ok=True) + + original_elements = partition_pdf( + filename=pdf_path, + strategy=strategy, + include_page_breaks=True, + sort_mode=SORT_MODE_BASIC, + ) + draw_elements(original_elements, images, output_type, output_dir, f_base_name, "original") + + ordered_elements = partition_pdf( + filename=pdf_path, + strategy=strategy, + include_page_breaks=True, + sort_mode=SORT_MODE_XY_CUT, + ) + draw_elements(ordered_elements, images, output_type, output_dir, f_base_name, "result") + print("<<< Finished run_partition_pdf") + + +def run(): + f_sub_path = sys.argv[1] + strategy = sys.argv[2] + + base_dir = os.getcwd() + output_root_dir = os.path.join(base_dir, "examples", "custom-layout-order", "output") + os.makedirs(output_root_dir, exist_ok=True) + + f_path = os.path.join(base_dir, f_sub_path) + images = pdf2image.convert_from_path(f_path) + run_partition_pdf(f_path, strategy, images, "image", output_root_dir) + + +if __name__ == '__main__': + if len(sys.argv) < 3: + print( + "Please provide the path to the file name as the first argument and the strategy as the " + "second argument.", + ) + sys.exit(1) + + run() diff --git a/test_unstructured/file_utils/test_filetype.py b/test_unstructured/file_utils/test_filetype.py index 752d92dcbe..60451c971a 100644 --- a/test_unstructured/file_utils/test_filetype.py +++ b/test_unstructured/file_utils/test_filetype.py @@ -4,19 +4,14 @@ import magic import pytest -from PIL import Image -from unstructured_inference.inference import layout -from unstructured_inference.inference.layoutelement import LocationlessLayoutElement from unstructured.file_utils import filetype from unstructured.file_utils.filetype import ( FileType, - _get_page_image_metadata, _is_code_mime_type, _is_text_file_a_csv, _is_text_file_a_json, detect_filetype, - document_to_element_list, ) FILE_DIRECTORY = pathlib.Path(__file__).parent.resolve() @@ -31,29 +26,6 @@ ] -class MockPageLayout(layout.PageLayout): - def __init__(self, number: int, image: Image): - self.number = number - self.image = image - - @property - def elements(self): - return [ - LocationlessLayoutElement( - type="Headline", - text="Charlie Brown and the Great Pumpkin", - ), - ] - - -class MockDocumentLayout(layout.DocumentLayout): - @property - def pages(self): - return [ - MockPageLayout(number=1, image=Image.new("1", (1, 1))), - ] - - @pytest.mark.parametrize( ("file", "expected"), [ @@ -467,15 +439,3 @@ def test_detect_filetype_skips_escape_commas_for_csv(tmpdir): with open(filename, "rb") as f: assert detect_filetype(file=f) == FileType.CSV - - -def test_document_to_element_list_omits_coord_system_when_coord_points_absent(): - layout_elem_absent_coordinates = MockDocumentLayout() - elements = document_to_element_list(layout_elem_absent_coordinates) - assert elements[0].metadata.coordinates is None - - -def test_get_page_image_metadata_and_coordinate_system(): - doc = MockDocumentLayout() - metadata = _get_page_image_metadata(doc.pages[0]) - assert isinstance(metadata, dict) diff --git a/test_unstructured/partition/pdf-image/test_pdf.py b/test_unstructured/partition/pdf-image/test_pdf.py index 60bceead19..736868af7c 100644 --- a/test_unstructured/partition/pdf-image/test_pdf.py +++ b/test_unstructured/partition/pdf-image/test_pdf.py @@ -470,10 +470,10 @@ def test_partition_pdf_fast_groups_text_in_text_box(): assert str(elements[1]).endswith("Jordan and Egypt.") expected_coordinate_points_3 = ( - (273.9929, 181.16470000000004), - (273.9929, 226.16470000000004), - (333.59990000000005, 226.16470000000004), - (333.59990000000005, 181.16470000000004), + (95.6683, 181.16470000000004), + (95.6683, 226.16470000000004), + (166.7908, 226.16470000000004), + (166.7908, 181.16470000000004), ) expected_coordinate_system_3 = PixelSpace(width=612, height=792) expected_elem_metadata_3 = ElementMetadata( @@ -482,7 +482,7 @@ def test_partition_pdf_fast_groups_text_in_text_box(): system=expected_coordinate_system_3, ), ) - assert elements[3] == Title("1st", metadata=expected_elem_metadata_3) + assert elements[3] == Text("2.5", metadata=expected_elem_metadata_3) def test_partition_pdf_with_metadata_filename( diff --git a/test_unstructured/partition/test_common.py b/test_unstructured/partition/test_common.py index e1acc9355f..1d46467f8f 100644 --- a/test_unstructured/partition/test_common.py +++ b/test_unstructured/partition/test_common.py @@ -1,5 +1,8 @@ import pytest +from PIL import Image +from unstructured_inference.inference import layout from unstructured_inference.inference.layout import LayoutElement +from unstructured_inference.inference.layoutelement import LocationlessLayoutElement from unstructured.documents.coordinates import PixelSpace from unstructured.documents.elements import ( @@ -11,7 +14,34 @@ Title, ) from unstructured.partition import common -from unstructured.partition.common import contains_emoji +from unstructured.partition.common import ( + _get_page_image_metadata, + contains_emoji, + document_to_element_list, +) + + +class MockPageLayout(layout.PageLayout): + def __init__(self, number: int, image: Image): + self.number = number + self.image = image + + @property + def elements(self): + return [ + LocationlessLayoutElement( + type="Headline", + text="Charlie Brown and the Great Pumpkin", + ), + ] + + +class MockDocumentLayout(layout.DocumentLayout): + @property + def pages(self): + return [ + MockPageLayout(number=1, image=Image.new("1", (1, 1))), + ] def test_normalize_layout_element_dict(): @@ -243,3 +273,15 @@ def test_convert_ms_office_table_to_text_works_with_empty_tables(): ) def test_contains_emoji(text, expected): assert contains_emoji(text) is expected + + +def test_document_to_element_list_omits_coord_system_when_coord_points_absent(): + layout_elem_absent_coordinates = MockDocumentLayout() + elements = document_to_element_list(layout_elem_absent_coordinates) + assert elements[0].metadata.coordinates is None + + +def test_get_page_image_metadata_and_coordinate_system(): + doc = MockDocumentLayout() + metadata = _get_page_image_metadata(doc.pages[0]) + assert isinstance(metadata, dict) diff --git a/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.pdf.json b/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.pdf.json index a0f7dac8f1..9d2ca1db89 100644 --- a/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.pdf.json @@ -30,294 +30,294 @@ "text": "(Section references are to the Internal Revenue Code unless otherwise noted.)" }, { - "type": "ListItem", - "element_id": "14e8cc92f6875b7562c7b37b363a4271", + "type": "Title", + "element_id": "61ed58fa51293f429f87e8cf1896c9e4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Long-term contracts. —If you are required to change your method of accounting for long-term contracts under section" + "text": "Paperwork Reduction Act Notice" }, { - "type": "ListItem", - "element_id": "ac843848ae2f4c656203dee90cdc207c", + "type": "NarrativeText", + "element_id": "828767cbc922e731b59894afba55fe10", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ", see Notice" + "text": "We ask for this information to carry out the Internal Revenue laws of the United States. We need it to ensure that taxpayers are complying with these laws and to allow us to figure and collect the right amount of tax. You are required to give us this information." }, { - "type": "ListItem", - "element_id": "3973e022e93220f9212c18d0d0c543ae", + "type": "Title", + "element_id": "a1547a4ed1611eee44b15e99120fb978", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "-" + "text": "General Instructions" }, { - "type": "ListItem", - "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", + "type": "Title", + "element_id": "68a3289177b49b285e133a5267eb355f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "(" + "text": "Purpose of Form" }, { - "type": "ListItem", - "element_id": "8a5edab282632443219e051e4ade2d1d", + "type": "NarrativeText", + "element_id": "84e7e32f584e2ee9f47ba593bf86c559", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "/" + "text": "Generally, applicants must complete Section A. In addition, complete the appropriate sections (B-1 through H) for which a change Is desired." }, { "type": "ListItem", - "element_id": "8a5edab282632443219e051e4ade2d1d", + "element_id": "178d6933ed193747b1c4aa1c048e7f94", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "/" + "text": "for these changes." }, { "type": "ListItem", - "element_id": "bb01c44bd646ab29df9cea6459a3499b", + "element_id": "29b33c1e0aea8247e6576bd9ad14448e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ")," + "text": "IRB" }, { "type": "ListItem", - "element_id": "3973e022e93220f9212c18d0d0c543ae", + "element_id": "ac843848ae2f4c656203dee90cdc207c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "-" + "text": ", see Notice" }, { "type": "ListItem", - "element_id": "29b33c1e0aea8247e6576bd9ad14448e", + "element_id": "3973e022e93220f9212c18d0d0c543ae", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "IRB" + "text": "-" }, { "type": "ListItem", - "element_id": "2beea67e67a36c0708e98cba96d1779f", + "element_id": "8a5edab282632443219e051e4ade2d1d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ", for the notification procedures that must be followed. Other methods.—Unless the Service has published a regulation or procedure to the contrary, all other changes !n accounting methods required by the Act are automatically considered to be approved by the Commissioner. Examples of method changes automatically approved by the Commissioner are those changes required to effect: (" + "text": "/" }, { "type": "ListItem", - "element_id": "5157d731aa6a97c9b166799db2295bce", + "element_id": "8a5edab282632443219e051e4ade2d1d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ") the repeal of the reserve method for bad debts of taxpayers other than financial institutions (Act section" + "text": "/" }, { "type": "ListItem", - "element_id": "fd0f38844b9901d3a4e7c44630346145", + "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "); (" + "text": "(" }, { "type": "ListItem", - "element_id": "34b66452ca63c465c69d849e4acf6d46", + "element_id": "3973e022e93220f9212c18d0d0c543ae", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ") the repeal of the installment method for sales under a revolving credit plan (Act section" + "text": "-" }, { "type": "ListItem", - "element_id": "fd0f38844b9901d3a4e7c44630346145", + "element_id": "14e8cc92f6875b7562c7b37b363a4271", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "); (" + "text": "Long-term contracts. —If you are required to change your method of accounting for long-term contracts under section" }, { "type": "ListItem", - "element_id": "353b10e26575591f537f9718242cd574", + "element_id": "2beea67e67a36c0708e98cba96d1779f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ") the Inclusion of income attributable to the sale or furnishing of utility services no later than the year In which the services were provided to customers (Act section" + "text": ", for the notification procedures that must be followed. Other methods.—Unless the Service has published a regulation or procedure to the contrary, all other changes !n accounting methods required by the Act are automatically considered to be approved by the Commissioner. Examples of method changes automatically approved by the Commissioner are those changes required to effect: (" }, { "type": "ListItem", - "element_id": "25d6eaf57eebce49267b71ce2f347a03", + "element_id": "fd0f38844b9901d3a4e7c44630346145", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "); and (" + "text": "); (" }, { "type": "ListItem", - "element_id": "13f155c0754434406190f3cf49c82c3c", + "element_id": "34b66452ca63c465c69d849e4acf6d46", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": ") the repeal of the deduction for qualified discount coupons (Act section" + "text": ") the repeal of the installment method for sales under a revolving credit plan (Act section" }, { "type": "ListItem", - "element_id": "e9d9ab5eb5ff32a31a32bda940a33b7a", + "element_id": "bb01c44bd646ab29df9cea6459a3499b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "). Do not file Form" + "text": ")," }, { "type": "ListItem", - "element_id": "178d6933ed193747b1c4aa1c048e7f94", + "element_id": "13f155c0754434406190f3cf49c82c3c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "for these changes." + "text": ") the repeal of the deduction for qualified discount coupons (Act section" }, { - "type": "Title", - "element_id": "61ed58fa51293f429f87e8cf1896c9e4", + "type": "ListItem", + "element_id": "fd0f38844b9901d3a4e7c44630346145", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Paperwork Reduction Act Notice" + "text": "); (" }, { - "type": "Title", - "element_id": "f1a73e2204a114077f988c9da98d7f8b", + "type": "ListItem", + "element_id": "353b10e26575591f537f9718242cd574", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Signature" + "text": ") the Inclusion of income attributable to the sale or furnishing of utility services no later than the year In which the services were provided to customers (Act section" }, { "type": "ListItem", - "element_id": "f09181ea8ac5d177b8d2f79bbae03f18", + "element_id": "25d6eaf57eebce49267b71ce2f347a03", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Signature Individuals. —An individual desiring the change should sign the application. If the application pertains to a husband and wife filing a joint income tax return, the names of both should appear in the heading and both should sign. Partnerships.—The form should be signed with the partnership name followed by the signature of one of the general partners and the words “General Partner.” Corporations, cooperatives, and insurance companies.—The form should show the name of the corporation, cooperative, or insurance company and the signature of the president, vice president, treasurer, assistant treasurer, or chief accounting officer (such as tax officer) authorized to sign, and his or her official title. Receivers, trustees, or assignees must sign any application they are required to file. For a subsidiary corporation filing a consolidated return with its parent, the form should be signed by an officer of the parent corporation. Fiduciaries.—The-form should show the name of the estate or trust and be signed by the fiduciary, personal representative, executor, executrix, administrator, administratrix, etc., having legal authority to sign, and his or her title. Preparer other than partner, officer, etc.—The signature of the individual preparing the application should appear in the space provided on page" + "text": "); and (" }, { "type": "ListItem", - "element_id": "586e989b479e4362ebe28a6954c1427b", + "element_id": "5157d731aa6a97c9b166799db2295bce", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "If the individual or firm is also authorized to" + "text": ") the repeal of the reserve method for bad debts of taxpayers other than financial institutions (Act section" }, { - "type": "NarrativeText", - "element_id": "828767cbc922e731b59894afba55fe10", + "type": "ListItem", + "element_id": "e9d9ab5eb5ff32a31a32bda940a33b7a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "We ask for this information to carry out the Internal Revenue laws of the United States. We need it to ensure that taxpayers are complying with these laws and to allow us to figure and collect the right amount of tax. You are required to give us this information." + "text": "). Do not file Form" }, { "type": "Title", - "element_id": "a1547a4ed1611eee44b15e99120fb978", + "element_id": "af8bdf713f162b09567c8d1a3a2d4de7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "General Instructions" + "text": "Generally, applicants must file this form within the first 180 days of the tax year in which it is desired to make the change." }, { "type": "Title", - "element_id": "68a3289177b49b285e133a5267eb355f", + "element_id": "5756fb398995bb6518a87637f24f426e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Purpose of Form" + "text": "Time and Place for Filing" }, { - "type": "NarrativeText", - "element_id": "84e7e32f584e2ee9f47ba593bf86c559", + "type": "ListItem", + "element_id": "f09181ea8ac5d177b8d2f79bbae03f18", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Generally, applicants must complete Section A. In addition, complete the appropriate sections (B-1 through H) for which a change Is desired." + "text": "Signature Individuals. —An individual desiring the change should sign the application. If the application pertains to a husband and wife filing a joint income tax return, the names of both should appear in the heading and both should sign. Partnerships.—The form should be signed with the partnership name followed by the signature of one of the general partners and the words “General Partner.” Corporations, cooperatives, and insurance companies.—The form should show the name of the corporation, cooperative, or insurance company and the signature of the president, vice president, treasurer, assistant treasurer, or chief accounting officer (such as tax officer) authorized to sign, and his or her official title. Receivers, trustees, or assignees must sign any application they are required to file. For a subsidiary corporation filing a consolidated return with its parent, the form should be signed by an officer of the parent corporation. Fiduciaries.—The-form should show the name of the estate or trust and be signed by the fiduciary, personal representative, executor, executrix, administrator, administratrix, etc., having legal authority to sign, and his or her title. Preparer other than partner, officer, etc.—The signature of the individual preparing the application should appear in the space provided on page" }, { - "type": "Title", - "element_id": "5756fb398995bb6518a87637f24f426e", + "type": "ListItem", + "element_id": "586e989b479e4362ebe28a6954c1427b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Time and Place for Filing" + "text": "If the individual or firm is also authorized to" }, { "type": "Title", - "element_id": "af8bdf713f162b09567c8d1a3a2d4de7", + "element_id": "f1a73e2204a114077f988c9da98d7f8b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Generally, applicants must file this form within the first 180 days of the tax year in which it is desired to make the change." + "text": "Signature" }, { "type": "Title", @@ -331,23 +331,23 @@ }, { "type": "Title", - "element_id": "8b06cd6e2bf7fc15130d5d9ed7e66283", + "element_id": "242a9dba10a04654d4adef9c58ff96f6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Affiliated Groups" + "text": "Changes to Accounting Methods Required Under the Tax Reform Act of 1986" }, { "type": "Title", - "element_id": "242a9dba10a04654d4adef9c58ff96f6", + "element_id": "8b06cd6e2bf7fc15130d5d9ed7e66283", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Changes to Accounting Methods Required Under the Tax Reform Act of 1986" + "text": "Affiliated Groups" }, { "type": "Title", @@ -420,54 +420,54 @@ "text": "Section E" }, { - "type": "ListItem", - "element_id": "dfca5da56b8cdb627309e2aa5a45e17b", + "type": "NarrativeText", + "element_id": "1bbe995811e9fd4c3ce1b218cb641f4e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Section" + "text": "(1) Gives your best estimate of the percentage of the section 481(a) adjustment that would have been required if the requested change had been made for each of the 3 preceding years; and" }, { - "type": "ListItem", - "element_id": "b9c2a964cd107c5155ef70e5b235a05d", + "type": "NarrativeText", + "element_id": "2de8f0b5003bcb8c12a4dc59c8e1f740", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(f) provides that the term “long-term contract” means any contract for the manufacturing, building, installation, or construction of property that is not completed within the tax year in which it" + "text": "See section 5.06(2) of Rev. Proc. 84-74 for the required perjury statement that must be attached." }, { - "type": "ListItem", - "element_id": "8e69cd6874d876dce416a44e695b58eb", + "type": "NarrativeText", + "element_id": "751abc8c6a0fa412c3e8c18345f57f95", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "s entered into. However, a manufacturing contract will not qualify as a long-term contract unless the contract involves the manufacture of: (" + "text": "Item 13, page 2.—Insert the actual number of tax years. Use of the term “since inception” 1s not acceptable. However, “more than 6 years” Is acceptable." }, { - "type": "ListItem", - "element_id": "1b69bc9514700ed89e0af2872cbb95c8", + "type": "Title", + "element_id": "53e33d10c9df4a570490182ccef0cd95", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") a unique item not normally included in your finished goods inventory, or (" + "text": "Section C" }, { "type": "ListItem", - "element_id": "aaa7abdc10628a69ab04fcea8ecdc29d", + "element_id": "dfca5da56b8cdb627309e2aa5a45e17b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") any item that normally requires more than" + "text": "Section" }, { "type": "ListItem", @@ -480,44 +480,44 @@ "text": "calendar months to complete." }, { - "type": "NarrativeText", - "element_id": "1bbe995811e9fd4c3ce1b218cb641f4e", + "type": "ListItem", + "element_id": "aaa7abdc10628a69ab04fcea8ecdc29d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(1) Gives your best estimate of the percentage of the section 481(a) adjustment that would have been required if the requested change had been made for each of the 3 preceding years; and" + "text": ") any item that normally requires more than" }, { "type": "ListItem", - "element_id": "91057a4a80779d62b06d27fdce5da42c", + "element_id": "1b69bc9514700ed89e0af2872cbb95c8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "All long-term contracts entered into after February" + "text": ") a unique item not normally included in your finished goods inventory, or (" }, { "type": "ListItem", - "element_id": "d03502c43d74a30b936740a9517dc4ea", + "element_id": "8e69cd6874d876dce416a44e695b58eb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "," + "text": "s entered into. However, a manufacturing contract will not qualify as a long-term contract unless the contract involves the manufacture of: (" }, { "type": "ListItem", - "element_id": "7613695d576752ab22ae7c02866cf1e3", + "element_id": "b9c2a964cd107c5155ef70e5b235a05d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ", except for real property construction contracts expected to be completed within" + "text": "(f) provides that the term “long-term contract” means any contract for the manufacturing, building, installation, or construction of property that is not completed within the tax year in which it" }, { "type": "ListItem", @@ -531,13 +531,13 @@ }, { "type": "ListItem", - "element_id": "f2923844fb3e4992f1c6ddd808867d96", + "element_id": "dcf589bb37d079ecce4b375abc332606", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "prior tax years do not exceed $" + "text": "Caution: At the time these instructions were printed, Congress was considering legislation that would repeal the use of the percentage of completion-capitalized cost method for certain long-term contracts." }, { "type": "ListItem", @@ -551,63 +551,63 @@ }, { "type": "ListItem", - "element_id": "d03502c43d74a30b936740a9517dc4ea", + "element_id": "7613695d576752ab22ae7c02866cf1e3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "," + "text": ", except for real property construction contracts expected to be completed within" }, { "type": "ListItem", - "element_id": "4df00d9659b3bfaac5990114275c4bf5", + "element_id": "91057a4a80779d62b06d27fdce5da42c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ", must be accounted for using either the percentage of completion- capitalized cost method or the percentage of completion method. See section" + "text": "All long-term contracts entered into after February" }, { "type": "ListItem", - "element_id": "dcf589bb37d079ecce4b375abc332606", + "element_id": "f2923844fb3e4992f1c6ddd808867d96", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Caution: At the time these instructions were printed, Congress was considering legislation that would repeal the use of the percentage of completion-capitalized cost method for certain long-term contracts." + "text": "prior tax years do not exceed $" }, { - "type": "NarrativeText", - "element_id": "2de8f0b5003bcb8c12a4dc59c8e1f740", + "type": "ListItem", + "element_id": "4df00d9659b3bfaac5990114275c4bf5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "See section 5.06(2) of Rev. Proc. 84-74 for the required perjury statement that must be attached." + "text": ", must be accounted for using either the percentage of completion- capitalized cost method or the percentage of completion method. See section" }, { - "type": "NarrativeText", - "element_id": "751abc8c6a0fa412c3e8c18345f57f95", + "type": "ListItem", + "element_id": "d03502c43d74a30b936740a9517dc4ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Item 13, page 2.—Insert the actual number of tax years. Use of the term “since inception” 1s not acceptable. However, “more than 6 years” Is acceptable." + "text": "," }, { - "type": "Title", - "element_id": "53e33d10c9df4a570490182ccef0cd95", + "type": "ListItem", + "element_id": "d03502c43d74a30b936740a9517dc4ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Section C" + "text": "," }, { "type": "Title", @@ -659,16 +659,6 @@ }, "text": "corporations, partnerships with a C corporation as a partner, and tax shelters may not use the cash method of accounting. For purposes of this limitation, a trust subject to the tax on unrelated business income under section 511 1s treated as aC corporation with respect to its unrelated trade or business activities." }, - { - "type": "Title", - "element_id": "a8155ab3bed92cc259ab58331619e0e1", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 2 - }, - "text": "Section H" - }, { "type": "NarrativeText", "element_id": "e5bed7fe04dd22cabe5e5c0362d37743", @@ -681,93 +671,93 @@ }, { "type": "ListItem", - "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", + "element_id": "70360b86614c25f67ca8959ac00d5389", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(" + "text": "requires certain C corporations and partnerships with a C corporation as a partner to use the accrual method." }, { "type": "ListItem", - "element_id": "e388a9c123531db35a336ca587dc1a78", + "element_id": "91621b3a2068ab97aafa195a272a663e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") Farming businesses.—F or this purpose, the term “farming business”" + "text": ") applies. Notwithstanding this exception, section" }, { "type": "ListItem", - "element_id": "ff9c1c0798a1d593d7b89253052fc17f", + "element_id": "7c2c864009e421aecec36fd061644f50", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "s defined in section" + "text": "A(c)(" }, { "type": "ListItem", - "element_id": "cac62e982bd6f2fdde9219ae1aff4c92", + "element_id": "124f8e567bb2fc32647f9a44201e0688", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "A(e)(" + "text": "), but it also includes the raising, harvesting, or growing of trees to which section" }, { "type": "ListItem", - "element_id": "124f8e567bb2fc32647f9a44201e0688", + "element_id": "e388a9c123531db35a336ca587dc1a78", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "), but it also includes the raising, harvesting, or growing of trees to which section" + "text": ") Farming businesses.—F or this purpose, the term “farming business”" }, { "type": "ListItem", - "element_id": "7c2c864009e421aecec36fd061644f50", + "element_id": "ff9c1c0798a1d593d7b89253052fc17f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "A(c)(" + "text": "s defined in section" }, { "type": "ListItem", - "element_id": "91621b3a2068ab97aafa195a272a663e", + "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") applies. Notwithstanding this exception, section" + "text": "(" }, { "type": "ListItem", - "element_id": "70360b86614c25f67ca8959ac00d5389", + "element_id": "cac62e982bd6f2fdde9219ae1aff4c92", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "requires certain C corporations and partnerships with a C corporation as a partner to use the accrual method." + "text": "A(e)(" }, { "type": "NarrativeText", - "element_id": "86d11953bb813a770ecd242ff97d4e43", + "element_id": "0607edfa2419dd0cdc80f457872fe238", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "If you are making an election under section 458, show the applicable information under Regulations section 1.458-10." + "text": "(2) Qualified personal service corporations. — A “qualified personal service corporation” is any corporation: (a) substantially all of the activities of which involve the performance of services in the fields of health, law," }, { "type": "Title", @@ -779,14 +769,24 @@ }, "text": "Section D" }, + { + "type": "Title", + "element_id": "a8155ab3bed92cc259ab58331619e0e1", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 2 + }, + "text": "Section H" + }, { "type": "NarrativeText", - "element_id": "0607edfa2419dd0cdc80f457872fe238", + "element_id": "86d11953bb813a770ecd242ff97d4e43", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(2) Qualified personal service corporations. — A “qualified personal service corporation” is any corporation: (a) substantially all of the activities of which involve the performance of services in the fields of health, law," + "text": "If you are making an election under section 458, show the applicable information under Regulations section 1.458-10." } ] \ No newline at end of file diff --git a/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.png.json b/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.png.json index 09e9c57225..e25c248520 100644 --- a/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.png.json +++ b/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.png.json @@ -20,84 +20,84 @@ "text": "(Section references are to the Internal Revenue Code unless otherwise noted.)" }, { - "type": "ListItem", - "element_id": "36a565493a214d3f7e7f24794c1dc7f4", + "type": "Title", + "element_id": "61ed58fa51293f429f87e8cf1896c9e4", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Long-term contracts.—If you are required to change your method of accounting for long-term contracts under section" + "text": "Paperwork Reduction Act Notice" }, { - "type": "ListItem", - "element_id": "ac843848ae2f4c656203dee90cdc207c", + "type": "NarrativeText", + "element_id": "4660422c06dddc914ab634c5e4045dec", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ", see Notice" + "text": "We ask for this information to carry out the Internal Revenue laws of the United States. We need it to ensure that taxpayers are complying with these laws an¢ to allow us to figure and collect the nght amount of tax. You are required to give us this information." }, { - "type": "ListItem", - "element_id": "3973e022e93220f9212c18d0d0c543ae", + "type": "Title", + "element_id": "a1547a4ed1611eee44b15e99120fb978", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "-" + "text": "General Instructions" }, { - "type": "ListItem", - "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", + "type": "Title", + "element_id": "68a3289177b49b285e133a5267eb355f", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "(" + "text": "Purpose of Form" }, { - "type": "ListItem", - "element_id": "8a5edab282632443219e051e4ade2d1d", + "type": "NarrativeText", + "element_id": "f9b8e17da7a31507773f78959378e09c", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "/" + "text": "File this form to request a change in your accounting method, including the accounting treatment of any item. if you are requesting 2 change in accounting period, use Form 1128, Application for Change in Accounting Period. For more information, see Publication 538, Accounting Periods and Methods," }, { - "type": "ListItem", - "element_id": "8a5edab282632443219e051e4ade2d1d", + "type": "NarrativeText", + "element_id": "b3859f2f29884b1d3ba0892e52859a99", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "/" + "text": "When filing Form 3115, taxpayers are reminded to determine if IRS has published a ruling or procedure dealing with the specific type of change since November 1987 (the current. revision date of Form 3115)" }, { - "type": "ListItem", - "element_id": "bb01c44bd646ab29df9cea6459a3499b", + "type": "NarrativeText", + "element_id": "e5a95dc10d4071983b70898a21f11175", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ")," + "text": "Generally, applicants must complete Section ‘A. In addition, complete the appropriate sections (B:1 through H) for which a change is desired." }, { "type": "ListItem", - "element_id": "3973e022e93220f9212c18d0d0c543ae", + "element_id": "e9d9ab5eb5ff32a31a32bda940a33b7a", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "-" + "text": "). Do not file Form" }, { "type": "ListItem", @@ -111,213 +111,213 @@ }, { "type": "ListItem", - "element_id": "59bc2945a7f606bd5078bac3bc1199d4", + "element_id": "36a565493a214d3f7e7f24794c1dc7f4", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ", for the notification procedures that must be followed. Other methods. —Unless the Service has published a regulation or procedure to the contrary, all other changes in accounting methods required by the Act are automatically considered to be approved by the Commissioner. Examples of method changes automatically approved by the Commissioner are those changes required to effect: (" + "text": "Long-term contracts.—If you are required to change your method of accounting for long-term contracts under section" }, { "type": "ListItem", - "element_id": "5157d731aa6a97c9b166799db2295bce", + "element_id": "ac843848ae2f4c656203dee90cdc207c", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ") the repeal of the reserve method for bad debts of taxpayers other than financial institutions (Act section" + "text": ", see Notice" }, { "type": "ListItem", - "element_id": "fd0f38844b9901d3a4e7c44630346145", + "element_id": "3973e022e93220f9212c18d0d0c543ae", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "); (" + "text": "-" }, { "type": "ListItem", - "element_id": "34b66452ca63c465c69d849e4acf6d46", + "element_id": "8a5edab282632443219e051e4ade2d1d", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ") the repeal of the installment method for sales under a revolving credit plan (Act section" + "text": "/" }, { "type": "ListItem", - "element_id": "fd0f38844b9901d3a4e7c44630346145", + "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "); (" + "text": "(" }, { "type": "ListItem", - "element_id": "b0fa5aaff0cee8574822dd8ac6537c06", + "element_id": "bb01c44bd646ab29df9cea6459a3499b", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ") the Inclusion of mcome attributable to the sale or furnishing of utility services no later than the year in which the services were provided to customers (Act section" + "text": ")," }, { "type": "ListItem", - "element_id": "25d6eaf57eebce49267b71ce2f347a03", + "element_id": "3973e022e93220f9212c18d0d0c543ae", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "); and (" + "text": "-" }, { "type": "ListItem", - "element_id": "13f155c0754434406190f3cf49c82c3c", + "element_id": "59bc2945a7f606bd5078bac3bc1199d4", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": ") the repeal of the deduction for qualified discount coupons (Act section" + "text": ", for the notification procedures that must be followed. Other methods. —Unless the Service has published a regulation or procedure to the contrary, all other changes in accounting methods required by the Act are automatically considered to be approved by the Commissioner. Examples of method changes automatically approved by the Commissioner are those changes required to effect: (" }, { "type": "ListItem", - "element_id": "e9d9ab5eb5ff32a31a32bda940a33b7a", + "element_id": "5157d731aa6a97c9b166799db2295bce", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "). Do not file Form" + "text": ") the repeal of the reserve method for bad debts of taxpayers other than financial institutions (Act section" }, { "type": "ListItem", - "element_id": "178d6933ed193747b1c4aa1c048e7f94", + "element_id": "fd0f38844b9901d3a4e7c44630346145", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "for these changes." + "text": "); (" }, { - "type": "NarrativeText", - "element_id": "7685df2334a5f6c8c8099dea61a8f1b4", + "type": "ListItem", + "element_id": "34b66452ca63c465c69d849e4acf6d46", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Long-term contracts.—If you are required to change your method of accounting for long-term contracts under section 460, see Notice 87-61 (9/21/87), 1987-38 IRB 40, for the notification procedures that must be followed." + "text": ") the repeal of the installment method for sales under a revolving credit plan (Act section" }, { - "type": "Title", - "element_id": "61ed58fa51293f429f87e8cf1896c9e4", + "type": "ListItem", + "element_id": "fd0f38844b9901d3a4e7c44630346145", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Paperwork Reduction Act Notice" + "text": "); (" }, { - "type": "Title", - "element_id": "55d4f33b09f24dd3b27865a5f34bfeb9", + "type": "ListItem", + "element_id": "b0fa5aaff0cee8574822dd8ac6537c06", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Signature tea" + "text": ") the Inclusion of mcome attributable to the sale or furnishing of utility services no later than the year in which the services were provided to customers (Act section" }, { "type": "ListItem", - "element_id": "5f8051f8010896bab02aaf784c04ae02", + "element_id": "25d6eaf57eebce49267b71ce2f347a03", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Individuals.—An individual desiring the change should sign the application. Ifthe application pertains to a husband and wife filing a joint Income tax return, the names of both should appear in the heading and both should sign Partnerships.—The form should be signed with the partnership name followed by the signature of one of the general partners and the words “General Partner.” Corporations, cooperatives, and insurance companies.—The form should show the name of the corporation, cooperative, or insurance Company and the signature of the president, vice president, treasurer, assistant treasurer, or chief accounting officer (such as tax officer) authorized tosign, and his or her official title. Receivers, trustees, or assignees must sign any application they are required to file, For a subsidiary corporation filing a consolidated return with its parent, the form should be signed by an officer of the parent corporation, Fiduciaries.—The-form should show the name of the estate or trust and be signed by the fiduciary, personal representative, executor, executrix, administrator, administratrx, etc’, having legal authority to'sign, and his or her ttle. Preparer other than partner, officer, etc.—The signature of the individual preparing the application should appear in the space provided on page" + "text": "); and (" }, { - "type": "NarrativeText", - "element_id": "4660422c06dddc914ab634c5e4045dec", + "type": "ListItem", + "element_id": "13f155c0754434406190f3cf49c82c3c", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "We ask for this information to carry out the Internal Revenue laws of the United States. We need it to ensure that taxpayers are complying with these laws an¢ to allow us to figure and collect the nght amount of tax. You are required to give us this information." + "text": ") the repeal of the deduction for qualified discount coupons (Act section" }, { - "type": "Title", - "element_id": "a1547a4ed1611eee44b15e99120fb978", + "type": "ListItem", + "element_id": "8a5edab282632443219e051e4ade2d1d", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "General Instructions" + "text": "/" }, { - "type": "Title", - "element_id": "68a3289177b49b285e133a5267eb355f", + "type": "ListItem", + "element_id": "178d6933ed193747b1c4aa1c048e7f94", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Purpose of Form" + "text": "for these changes." }, { "type": "NarrativeText", - "element_id": "f9b8e17da7a31507773f78959378e09c", + "element_id": "7685df2334a5f6c8c8099dea61a8f1b4", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "File this form to request a change in your accounting method, including the accounting treatment of any item. if you are requesting 2 change in accounting period, use Form 1128, Application for Change in Accounting Period. For more information, see Publication 538, Accounting Periods and Methods," + "text": "Long-term contracts.—If you are required to change your method of accounting for long-term contracts under section 460, see Notice 87-61 (9/21/87), 1987-38 IRB 40, for the notification procedures that must be followed." }, { - "type": "NarrativeText", - "element_id": "b3859f2f29884b1d3ba0892e52859a99", + "type": "Title", + "element_id": "5756fb398995bb6518a87637f24f426e", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "When filing Form 3115, taxpayers are reminded to determine if IRS has published a ruling or procedure dealing with the specific type of change since November 1987 (the current. revision date of Form 3115)" + "text": "Time and Place for Filing" }, { - "type": "NarrativeText", - "element_id": "e5a95dc10d4071983b70898a21f11175", + "type": "ListItem", + "element_id": "5f8051f8010896bab02aaf784c04ae02", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Generally, applicants must complete Section ‘A. In addition, complete the appropriate sections (B:1 through H) for which a change is desired." + "text": "Individuals.—An individual desiring the change should sign the application. Ifthe application pertains to a husband and wife filing a joint Income tax return, the names of both should appear in the heading and both should sign Partnerships.—The form should be signed with the partnership name followed by the signature of one of the general partners and the words “General Partner.” Corporations, cooperatives, and insurance companies.—The form should show the name of the corporation, cooperative, or insurance Company and the signature of the president, vice president, treasurer, assistant treasurer, or chief accounting officer (such as tax officer) authorized tosign, and his or her official title. Receivers, trustees, or assignees must sign any application they are required to file, For a subsidiary corporation filing a consolidated return with its parent, the form should be signed by an officer of the parent corporation, Fiduciaries.—The-form should show the name of the estate or trust and be signed by the fiduciary, personal representative, executor, executrix, administrator, administratrx, etc’, having legal authority to'sign, and his or her ttle. Preparer other than partner, officer, etc.—The signature of the individual preparing the application should appear in the space provided on page" }, { "type": "Title", - "element_id": "5756fb398995bb6518a87637f24f426e", + "element_id": "55d4f33b09f24dd3b27865a5f34bfeb9", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Time and Place for Filing" + "text": "Signature tea" }, { "type": "NarrativeText", @@ -331,23 +331,23 @@ }, { "type": "Title", - "element_id": "8b06cd6e2bf7fc15130d5d9ed7e66283", + "element_id": "242a9dba10a04654d4adef9c58ff96f6", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Affiliated Groups" + "text": "Changes to Accounting Methods Required Under the Tax Reform Act of 1986" }, { "type": "Title", - "element_id": "242a9dba10a04654d4adef9c58ff96f6", + "element_id": "8b06cd6e2bf7fc15130d5d9ed7e66283", "metadata": { "data_source": {}, "filetype": "image/png", "page_number": 1 }, - "text": "Changes to Accounting Methods Required Under the Tax Reform Act of 1986" + "text": "Affiliated Groups" }, { "type": "Title", diff --git a/test_unstructured_ingest/expected-structured-output/biomed-api/65/11/main.PMC6312790.pdf.json b/test_unstructured_ingest/expected-structured-output/biomed-api/65/11/main.PMC6312790.pdf.json index bd33d781b8..59b4926d7d 100644 --- a/test_unstructured_ingest/expected-structured-output/biomed-api/65/11/main.PMC6312790.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/biomed-api/65/11/main.PMC6312790.pdf.json @@ -100,34 +100,34 @@ "text": "a b s t r a c t" }, { - "type": "NarrativeText", - "element_id": "26c73759c3d3cc29d683910c034432da", + "type": "UncategorizedText", + "element_id": "4a03002c97925cd9397927ac823369e7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "This data article contains data related to the research article entitled “enhanced corrosion resistance of stainless steel Type 316 in sulphuric acid solution using eco-friendly waste product” (Sanni et al., 2018). In this data article, a comprehensive effect of waste product and optimized process parameter of the inhibitor in 0.5 M H2SO4 solution was presented using weight loss and potentiody- the inhibitor namic polarization techniques. The presence of (egg shell powder) influenced corrosion resistance of stainless steel. Inhibition efficiency value of 94.74% was recorded as a result of inhibition of the steel by the ionized molecules of the inhibiting compound of the egg shell powder influencing the redox mechan- ism reactions responsible for corrosion and surface deterioration." + "text": "Article history: Received 31 August 2018 Received in revised form 17 November 2018 Accepted 27 November 2018 Available online 30 November 2018" }, { "type": "UncategorizedText", - "element_id": "4a03002c97925cd9397927ac823369e7", + "element_id": "08bb309957586c280660c11c337dc6d7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Article history: Received 31 August 2018 Received in revised form 17 November 2018 Accepted 27 November 2018 Available online 30 November 2018" + "text": "Keywords: Corrosion Stainless steel Inhibitor Sulphuric acid" }, { - "type": "UncategorizedText", - "element_id": "08bb309957586c280660c11c337dc6d7", + "type": "NarrativeText", + "element_id": "26c73759c3d3cc29d683910c034432da", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Keywords: Corrosion Stainless steel Inhibitor Sulphuric acid" + "text": "This data article contains data related to the research article entitled “enhanced corrosion resistance of stainless steel Type 316 in sulphuric acid solution using eco-friendly waste product” (Sanni et al., 2018). In this data article, a comprehensive effect of waste product and optimized process parameter of the inhibitor in 0.5 M H2SO4 solution was presented using weight loss and potentiody- the inhibitor namic polarization techniques. The presence of (egg shell powder) influenced corrosion resistance of stainless steel. Inhibition efficiency value of 94.74% was recorded as a result of inhibition of the steel by the ionized molecules of the inhibiting compound of the egg shell powder influencing the redox mechan- ism reactions responsible for corrosion and surface deterioration." }, { "type": "UncategorizedText", @@ -201,23 +201,23 @@ }, { "type": "UncategorizedText", - "element_id": "8a54dcaa0e2720786903e26e84bd9e93", + "element_id": "78f135d64d5e1307cac651608256a418", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" + "text": "452" }, { "type": "UncategorizedText", - "element_id": "78f135d64d5e1307cac651608256a418", + "element_id": "8a54dcaa0e2720786903e26e84bd9e93", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "452" + "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" }, { "type": "UncategorizedText", @@ -230,54 +230,54 @@ "text": "How data were acquired" }, { - "type": "ListItem", - "element_id": "31579fc81cc53318d42fdeb413c08b20", + "type": "UncategorizedText", + "element_id": "682865ead44e65d8114a497f638af31d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "The cleaned and weighed specimen was suspended in beakers con- taining" + "text": "Data format Experimental factors" }, { - "type": "ListItem", - "element_id": "ab4b981b96a5176610e8eb85866b9c6c", + "type": "UncategorizedText", + "element_id": "c2e4d97e7f28b2ffd030ad2d8c1b4952", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "M H" + "text": "Experimental features Data source location" }, { - "type": "ListItem", - "element_id": "db052c8066385d54dc1aa02c83ea6cf6", + "type": "UncategorizedText", + "element_id": "802e93ca0ff6c12215598c216324f691", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "SO" + "text": "Accessibility Related research article" }, { "type": "ListItem", - "element_id": "ed735c7e194909033201e216d0a943da", + "element_id": "d4f85d36757c12f0c6dab57721287f32", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "solution of different concentrations of egg shell powder. The pre-weighed stainless steel samples were retrieved from the test solutions after every" + "text": "–" }, { "type": "ListItem", - "element_id": "f772412c7d7864de6602f0ddb4a354f2", + "element_id": "ba5ec51d07a4ac0e951608704431d59a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "h, cleaned appropriately, dried and reweighed. Raw, analyzed The difference between the weight at a given time and the initial weight of the specimen was taken as the weight loss, which was used to calculate the corrosion rate and inhibition efficiency. Inhibitor concentration, exposure time Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, Pretoria, South Africa Data are available within this article O. Sanni, A. P. I. Popoola, and O. S. I. Fayomi, Enhanced corrosion resistance of stainless steel type" + "text": ")" }, { "type": "ListItem", @@ -291,63 +291,63 @@ }, { "type": "ListItem", - "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", + "element_id": "f772412c7d7864de6602f0ddb4a354f2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(" + "text": "h, cleaned appropriately, dried and reweighed. Raw, analyzed The difference between the weight at a given time and the initial weight of the specimen was taken as the weight loss, which was used to calculate the corrosion rate and inhibition efficiency. Inhibitor concentration, exposure time Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, Pretoria, South Africa Data are available within this article O. Sanni, A. P. I. Popoola, and O. S. I. Fayomi, Enhanced corrosion resistance of stainless steel type" }, { "type": "ListItem", - "element_id": "ba5ec51d07a4ac0e951608704431d59a", + "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ")" + "text": "(" }, { "type": "ListItem", - "element_id": "d4f85d36757c12f0c6dab57721287f32", + "element_id": "db052c8066385d54dc1aa02c83ea6cf6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "–" + "text": "SO" }, { - "type": "UncategorizedText", - "element_id": "682865ead44e65d8114a497f638af31d", + "type": "ListItem", + "element_id": "ab4b981b96a5176610e8eb85866b9c6c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Data format Experimental factors" + "text": "M H" }, { - "type": "UncategorizedText", - "element_id": "c2e4d97e7f28b2ffd030ad2d8c1b4952", + "type": "ListItem", + "element_id": "31579fc81cc53318d42fdeb413c08b20", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Experimental features Data source location" + "text": "The cleaned and weighed specimen was suspended in beakers con- taining" }, { - "type": "UncategorizedText", - "element_id": "802e93ca0ff6c12215598c216324f691", + "type": "ListItem", + "element_id": "ed735c7e194909033201e216d0a943da", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Accessibility Related research article" + "text": "solution of different concentrations of egg shell powder. 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"text": "t h g e W" + "text": "20" }, { "type": "UncategorizedText", - "element_id": "50c393f158c3de2db92fa9661bfb00ed", + "element_id": "f82cec9d27e0eb21af4287cfc3f10c63", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i" + "text": "10g 8g 6g 4g 2g Control" }, { "type": "UncategorizedText", @@ -631,53 +631,53 @@ }, { "type": "UncategorizedText", - "element_id": "d2e181481b9515797bc42f282b122d25", + "element_id": "60f1f45902889fa87ac184f7dd16c609", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "1.8" + "text": "( e t a r n o s o r r o C" }, { "type": "UncategorizedText", - "element_id": "60f1f45902889fa87ac184f7dd16c609", + "element_id": "50c393f158c3de2db92fa9661bfb00ed", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "( e t a r n o s o r r o C" + "text": "i" }, { "type": "UncategorizedText", - "element_id": "f82cec9d27e0eb21af4287cfc3f10c63", + "element_id": "d2e181481b9515797bc42f282b122d25", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "10g 8g 6g 4g 2g Control" + "text": "1.8" }, { "type": "UncategorizedText", - "element_id": "50c393f158c3de2db92fa9661bfb00ed", + "element_id": "a839ab0447b2d415fe1732387938b5e0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i" + "text": "0.9" }, { "type": "UncategorizedText", - "element_id": "a839ab0447b2d415fe1732387938b5e0", + "element_id": "f82cec9d27e0eb21af4287cfc3f10c63", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "0.9" + "text": "10g 8g 6g 4g 2g Control" }, { "type": "UncategorizedText", @@ -801,113 +801,113 @@ }, { "type": "UncategorizedText", - "element_id": "6c2020fccd80e546787b8108268cd708", + "element_id": "fafba0527c3953c4b6e0e5b5739ba836", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "2g 4g 6g 8g 10g" + "text": ")" }, { "type": "UncategorizedText", - "element_id": "95aebc97bc646c67fdcd923a5965b001", + "element_id": "d14506655223461adf0b7bb605d29ca9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "80" + "text": "%" }, { "type": "UncategorizedText", - "element_id": "fafba0527c3953c4b6e0e5b5739ba836", + "element_id": "ac96469638e152a73cadbf62d44e2f39", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": ")" + "text": "(" }, { "type": "UncategorizedText", - "element_id": "d14506655223461adf0b7bb605d29ca9", + "element_id": "679d2bdce77a98d4cf4ad39b5c449e37", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "%" + "text": "y c n e c i f f" }, { "type": "UncategorizedText", - "element_id": "6442bc26a7c562f5afe6467dab36365c", + "element_id": "50c393f158c3de2db92fa9661bfb00ed", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "70" + "text": "i" }, { "type": "UncategorizedText", - "element_id": "ac96469638e152a73cadbf62d44e2f39", + "element_id": "bec5fc8721d3102a76fbe552feadf43c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "(" + "text": "E n o i t i b h n I" }, { "type": "UncategorizedText", - "element_id": "679d2bdce77a98d4cf4ad39b5c449e37", + "element_id": "50c393f158c3de2db92fa9661bfb00ed", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "y c n e c i f f" + "text": "i" }, { "type": "UncategorizedText", - "element_id": "95cf32708a31caa478a0e9141103ac56", + "element_id": "95aebc97bc646c67fdcd923a5965b001", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "60" + "text": "80" }, { "type": "UncategorizedText", - "element_id": "50c393f158c3de2db92fa9661bfb00ed", + "element_id": "6442bc26a7c562f5afe6467dab36365c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i" + "text": "70" }, { "type": "UncategorizedText", - "element_id": "7ea9844ae84eccbf55e8330640865e36", + "element_id": "95cf32708a31caa478a0e9141103ac56", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "50" + "text": "60" }, { "type": "UncategorizedText", - "element_id": "bec5fc8721d3102a76fbe552feadf43c", + "element_id": "7ea9844ae84eccbf55e8330640865e36", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "E n o i t i b h n I" + "text": "50" }, { "type": "UncategorizedText", @@ -921,23 +921,23 @@ }, { "type": "UncategorizedText", - "element_id": "50c393f158c3de2db92fa9661bfb00ed", + "element_id": "f4ccd05b3271c386ee55d9876c745001", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i" + "text": "30" }, { "type": "UncategorizedText", - "element_id": "f4ccd05b3271c386ee55d9876c745001", + "element_id": "6c2020fccd80e546787b8108268cd708", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "30" + "text": "2g 4g 6g 8g 10g" }, { "type": "UncategorizedText", @@ -1091,23 +1091,23 @@ }, { "type": "UncategorizedText", - "element_id": "8a54dcaa0e2720786903e26e84bd9e93", + "element_id": "8d9bcdac558e606c913189b6ce8db44c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" + "text": "454" }, { "type": "UncategorizedText", - "element_id": "8d9bcdac558e606c913189b6ce8db44c", + "element_id": "8a54dcaa0e2720786903e26e84bd9e93", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "454" + "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" }, { "type": "FigureCaption", @@ -1151,63 +1151,63 @@ }, { "type": "UncategorizedText", - "element_id": "110eda02dfff80619ea3b3d1fad86bbb", + "element_id": "123823735568c5aa326a4e80fd563f6c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "icorr (A/cm2)" + "text": "Inhibitor concentration (g)" }, { "type": "UncategorizedText", - "element_id": "30c9f72b1d5f5dbc66e82396ed69231f", + "element_id": "4d5dab59456c422bc87141a54ba83462", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Polarization resistance (Ω)" + "text": "0 2 4 6 8 10" }, { "type": "UncategorizedText", - "element_id": "8d3819e3016ef9656902e982ba48314f", + "element_id": "c97421108bb04b468a6a5c1db618650c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Corrosion rate (mm/year)" + "text": "bc (V/dec)" }, { "type": "UncategorizedText", - "element_id": "123823735568c5aa326a4e80fd563f6c", + "element_id": "711cc758cd65e30f33c0ceeec074fd35", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Inhibitor concentration (g)" + "text": "0.0335 1.9460 0.0163 0.3233 0.1240 0.0382" }, { "type": "UncategorizedText", - "element_id": "c97421108bb04b468a6a5c1db618650c", + "element_id": "f9ced859d08a94b4f5ad86061470b71f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "bc (V/dec)" + "text": "ba (V/dec)" }, { "type": "UncategorizedText", - "element_id": "f9ced859d08a94b4f5ad86061470b71f", + "element_id": "b7ea31af7a0498cf9a905c8726b9331c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "ba (V/dec)" + "text": "0.0409 0.0596 0.2369 0.0540 0.0556 0.0086" }, { "type": "UncategorizedText", @@ -1231,53 +1231,53 @@ }, { "type": "UncategorizedText", - "element_id": "4d5dab59456c422bc87141a54ba83462", + "element_id": "110eda02dfff80619ea3b3d1fad86bbb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0 2 4 6 8 10" + "text": "icorr (A/cm2)" }, { "type": "UncategorizedText", - "element_id": "711cc758cd65e30f33c0ceeec074fd35", + "element_id": "12cb80d1f0bdab43b690337371faa8fb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0.0335 1.9460 0.0163 0.3233 0.1240 0.0382" + "text": "0.0003 0.0002 0.0001 5.39E-05 5.46E-05 1.24E-05" }, { "type": "UncategorizedText", - "element_id": "b7ea31af7a0498cf9a905c8726b9331c", + "element_id": "30c9f72b1d5f5dbc66e82396ed69231f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0.0409 0.0596 0.2369 0.0540 0.0556 0.0086" + "text": "Polarization resistance (Ω)" }, { "type": "UncategorizedText", - "element_id": "12cb80d1f0bdab43b690337371faa8fb", + "element_id": "1b758dd8fe2bedd6c68145a88cf5f85c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0.0003 0.0002 0.0001 5.39E-05 5.46E-05 1.24E-05" + "text": "24.0910 121.440 42.121 373.180 305.650 246.080" }, { "type": "UncategorizedText", - "element_id": "1b758dd8fe2bedd6c68145a88cf5f85c", + "element_id": "8d3819e3016ef9656902e982ba48314f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "24.0910 121.440 42.121 373.180 305.650 246.080" + "text": "Corrosion rate (mm/year)" }, { "type": "UncategorizedText", @@ -1301,23 +1301,23 @@ }, { "type": "UncategorizedText", - "element_id": "d30a16d722f11b7f40f526a9f1909b4a", + "element_id": "a1fb50e6c86fae1679ef3351296fd671", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "C/0" + "text": "12" }, { "type": "UncategorizedText", - "element_id": "a1fb50e6c86fae1679ef3351296fd671", + "element_id": "d30a16d722f11b7f40f526a9f1909b4a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "12" + "text": "C/0" }, { "type": "UncategorizedText", @@ -1531,23 +1531,23 @@ }, { "type": "UncategorizedText", - "element_id": "8a54dcaa0e2720786903e26e84bd9e93", + "element_id": "cdfba543ee8ef7fdb3d8b587648cc22d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" + "text": "456" }, { "type": "UncategorizedText", - "element_id": "cdfba543ee8ef7fdb3d8b587648cc22d", + "element_id": "8a54dcaa0e2720786903e26e84bd9e93", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "456" + "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" }, { "type": "UncategorizedText", @@ -1631,43 +1631,43 @@ }, { "type": "UncategorizedText", - "element_id": "b84630a9e08df3b58aa3156c31355ffc", + "element_id": "66387f69a567df57abcbbcc378994a14", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "(cid:1) Þ ¼ 87:6W DAT" + "text": "Corrosion rate CRð" }, { "type": "UncategorizedText", - "element_id": "0c156d16287a78307e9e0220ead9ae3c", + "element_id": "b84630a9e08df3b58aa3156c31355ffc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "(cid:3)" + "text": "(cid:1) Þ ¼ 87:6W DAT" }, { "type": "UncategorizedText", - "element_id": "5ef0df6b867bd357888b9dc42b36cd2d", + "element_id": "0c156d16287a78307e9e0220ead9ae3c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "ð1Þ" + "text": "(cid:3)" }, { "type": "UncategorizedText", - "element_id": "66387f69a567df57abcbbcc378994a14", + "element_id": "5ef0df6b867bd357888b9dc42b36cd2d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "Corrosion rate CRð" + "text": "ð1Þ" }, { "type": "NarrativeText", @@ -1691,23 +1691,23 @@ }, { "type": "UncategorizedText", - "element_id": "0c29bf5278efb230950522e04cb5fc5e", + "element_id": "8c0cb198bc3c84fabd4fb5a938b8917c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "ð2Þ" + "text": "CRo" }, { "type": "UncategorizedText", - "element_id": "8c0cb198bc3c84fabd4fb5a938b8917c", + "element_id": "0c29bf5278efb230950522e04cb5fc5e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "CRo" + "text": "ð2Þ" }, { "type": "UncategorizedText", @@ -1721,43 +1721,43 @@ }, { "type": "UncategorizedText", - "element_id": "15fda6ea6b8bdae3400d8266245b2d00", + "element_id": "8c0cb198bc3c84fabd4fb5a938b8917c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "100 1" + "text": "CRo" }, { "type": "UncategorizedText", - "element_id": "cf99f6ed96eb26d3bce77491a6b07527", + "element_id": "73cb3858a687a8494ca3323053016282", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "ð3Þ" + "text": "x" }, { "type": "UncategorizedText", - "element_id": "73cb3858a687a8494ca3323053016282", + "element_id": "15fda6ea6b8bdae3400d8266245b2d00", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "x" + "text": "100 1" }, { "type": "UncategorizedText", - "element_id": "8c0cb198bc3c84fabd4fb5a938b8917c", + "element_id": "cf99f6ed96eb26d3bce77491a6b07527", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "CRo" + "text": "ð3Þ" }, { "type": "UncategorizedText", diff --git a/test_unstructured_ingest/expected-structured-output/biomed-api/75/29/main.PMC6312793.pdf.json b/test_unstructured_ingest/expected-structured-output/biomed-api/75/29/main.PMC6312793.pdf.json index dc329e930a..18c46c7049 100644 --- a/test_unstructured_ingest/expected-structured-output/biomed-api/75/29/main.PMC6312793.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/biomed-api/75/29/main.PMC6312793.pdf.json @@ -100,24 +100,24 @@ "text": "a b s t r a c t" }, { - "type": "NarrativeText", - "element_id": "dc4030a630e58a9d83ca4b1663c14a14", + "type": "UncategorizedText", + "element_id": "32133fc9f028473fb3d3d2ca24382c28", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "This data article presents a description of a benchmark dataset for the multiple depot vehicle scheduling problem (MDVSP). The MDVSP is to assign vehicles from different depots to timetabled trips to minimize the total cost of empty travel and waiting. The dataset has been developed to evaluate the heuristics of the MDVSP that are presented in “A new formulation and a column generation-based heuristic for the multiple depot vehicle sche- duling problem” (Kulkarni et al., 2018). The dataset contains 60 problem instances of varying size. Researchers can use the dataset to evaluate the future algorithms for the MDVSP and compare the performance with the existing algorithms. The dataset includes a program that can be used to generate new problem instances of the MDVSP." + "text": "Article history: Received 21 November 2018 Received in revised form 13 December 2018 Accepted 15 December 2018 Available online 18 December 2018" }, { - "type": "UncategorizedText", - "element_id": "32133fc9f028473fb3d3d2ca24382c28", + "type": "NarrativeText", + "element_id": "dc4030a630e58a9d83ca4b1663c14a14", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Article history: Received 21 November 2018 Received in revised form 13 December 2018 Accepted 15 December 2018 Available online 18 December 2018" + "text": "This data article presents a description of a benchmark dataset for the multiple depot vehicle scheduling problem (MDVSP). The MDVSP is to assign vehicles from different depots to timetabled trips to minimize the total cost of empty travel and waiting. The dataset has been developed to evaluate the heuristics of the MDVSP that are presented in “A new formulation and a column generation-based heuristic for the multiple depot vehicle sche- duling problem” (Kulkarni et al., 2018). The dataset contains 60 problem instances of varying size. Researchers can use the dataset to evaluate the future algorithms for the MDVSP and compare the performance with the existing algorithms. The dataset includes a program that can be used to generate new problem instances of the MDVSP." }, { "type": "UncategorizedText", @@ -200,54 +200,54 @@ "text": "Subject area Operations research More specific subject area Vehicle scheduling Type of data How data were acquired" }, { - "type": "ListItem", - "element_id": "bd2fe671326224907a8fb8062ddfede1", + "type": "UncategorizedText", + "element_id": "682865ead44e65d8114a497f638af31d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Tables, text files Artificially generated by a C þ þ program on Intels Xeons CPU E" + "text": "Data format Experimental factors" }, { - "type": "ListItem", - "element_id": "d4f85d36757c12f0c6dab57721287f32", + "type": "UncategorizedText", + "element_id": "0287da4a10649bec6dbc30dad29b9c88", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "–" + "text": "Experimental features Data source location Data accessibility Related research article" }, { "type": "ListItem", - "element_id": "4c94485e0c21ae6c41ce1dfe7b6bface", + "element_id": "803dac27c4823a821bc305f70dfa7a04", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "v" + "text": ", pp." }, { "type": "ListItem", - "element_id": "96aa227e395f9b3c693d4625454fd109", + "element_id": "1834b8a0cf841829856f3d93d0a40b8e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "with Linux operating system. Raw Sixty randomly generated instances of the MDVSP with the number of depots in (" + "text": "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem. Transportation Research Part B: Methodological," }, { "type": "ListItem", - "element_id": "d03502c43d74a30b936740a9517dc4ea", + "element_id": "bd8ec6ca4c7cf3541eeea741c731d6f4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "," + "text": ") Randomly generated instances IITB-Monash Research Academy, IIT Bombay, Powai, Mumbai, India. Data can be downloaded from https://orlib.uqcloud.net/ Kulkarni, S., Krishnamoorthy, M., Ranade, A., Ernst, A.T. and Patil, R.," }, { "type": "ListItem", @@ -261,33 +261,33 @@ }, { "type": "ListItem", - "element_id": "13695a46190f98abb2132499bd81dc3d", + "element_id": "d03502c43d74a30b936740a9517dc4ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") and the number of trips in (" + "text": "," }, { "type": "ListItem", - "element_id": "d03502c43d74a30b936740a9517dc4ea", + "element_id": "13695a46190f98abb2132499bd81dc3d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "," + "text": ") and the number of trips in (" }, { "type": "ListItem", - "element_id": "d03502c43d74a30b936740a9517dc4ea", + "element_id": "245843abef9e72e7efac30138a994bf6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "," + "text": "[" }, { "type": "ListItem", @@ -301,33 +301,33 @@ }, { "type": "ListItem", - "element_id": "bd8ec6ca4c7cf3541eeea741c731d6f4", + "element_id": "d03502c43d74a30b936740a9517dc4ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") Randomly generated instances IITB-Monash Research Academy, IIT Bombay, Powai, Mumbai, India. Data can be downloaded from https://orlib.uqcloud.net/ Kulkarni, S., Krishnamoorthy, M., Ranade, A., Ernst, A.T. and Patil, R.," + "text": "," }, { "type": "ListItem", - "element_id": "1834b8a0cf841829856f3d93d0a40b8e", + "element_id": "96aa227e395f9b3c693d4625454fd109", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem. Transportation Research Part B: Methodological," + "text": "with Linux operating system. Raw Sixty randomly generated instances of the MDVSP with the number of depots in (" }, { "type": "ListItem", - "element_id": "803dac27c4823a821bc305f70dfa7a04", + "element_id": "4c94485e0c21ae6c41ce1dfe7b6bface", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ", pp." + "text": "v" }, { "type": "ListItem", @@ -341,43 +341,43 @@ }, { "type": "ListItem", - "element_id": "245843abef9e72e7efac30138a994bf6", + "element_id": "bd2fe671326224907a8fb8062ddfede1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "[" + "text": "Tables, text files Artificially generated by a C þ þ program on Intels Xeons CPU E" }, { "type": "ListItem", - "element_id": "a00ad12fa538b6cae76f5413d3a14e45", + "element_id": "d03502c43d74a30b936740a9517dc4ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "]." + "text": "," }, { - "type": "UncategorizedText", - "element_id": "682865ead44e65d8114a497f638af31d", + "type": "ListItem", + "element_id": "d4f85d36757c12f0c6dab57721287f32", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Data format Experimental factors" + "text": "–" }, { - "type": "UncategorizedText", - "element_id": "0287da4a10649bec6dbc30dad29b9c88", + "type": "ListItem", + "element_id": "a00ad12fa538b6cae76f5413d3a14e45", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Experimental features Data source location Data accessibility Related research article" + "text": "]." }, { "type": "UncategorizedText", @@ -401,63 +401,63 @@ }, { "type": "UncategorizedText", - "element_id": "e58cc75666fbb70f7b25034fbf4f714e", + "element_id": "d32cdfe62dff9c818306e3ae5bbc43c0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "performance of the algorithms for the MDVSP." + "text": "(cid:2) The data provide all the information that is required to model the MDVSP by using the existing" }, { "type": "UncategorizedText", - "element_id": "d32cdfe62dff9c818306e3ae5bbc43c0", + "element_id": "e58cc75666fbb70f7b25034fbf4f714e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(cid:2) The data provide all the information that is required to model the MDVSP by using the existing" + "text": "performance of the algorithms for the MDVSP." }, { "type": "UncategorizedText", - "element_id": "85ab27a1f5be456597002c502432ef67", + "element_id": "bd5a257f5cf6d0ace1b6662efb4113c4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "mathematical formulations." + "text": "(cid:2) All the problem instances are available for use without any restrictions. (cid:2) The benchmark solutions and solution time for the problem instances are presented in [3] and can" }, { "type": "UncategorizedText", - "element_id": "bd5a257f5cf6d0ace1b6662efb4113c4", + "element_id": "85ab27a1f5be456597002c502432ef67", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(cid:2) All the problem instances are available for use without any restrictions. (cid:2) The benchmark solutions and solution time for the problem instances are presented in [3] and can" + "text": "mathematical formulations." }, { "type": "UncategorizedText", - "element_id": "e1b1668d8393547003869967247d4e94", + "element_id": "17c9d692a4b6c5103b1bb2d42176673e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "be used for the comparison." + "text": "(cid:2) The dataset includes a program that can generate similar problem instances of different sizes." }, { "type": "UncategorizedText", - "element_id": "17c9d692a4b6c5103b1bb2d42176673e", + "element_id": "e1b1668d8393547003869967247d4e94", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(cid:2) The dataset includes a program that can generate similar problem instances of different sizes." + "text": "be used for the comparison." }, { "type": "UncategorizedText", @@ -471,23 +471,23 @@ }, { "type": "UncategorizedText", - "element_id": "7de9f3c9c0c1cbf7dc40d9ba3d9cd3e6", + "element_id": "4443614d5e9dada0ac5245412ed35771", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "‘ðm; nÞ’," + "text": "the size," }, { "type": "UncategorizedText", - "element_id": "4443614d5e9dada0ac5245412ed35771", + "element_id": "7de9f3c9c0c1cbf7dc40d9ba3d9cd3e6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "the size," + "text": "‘ðm; nÞ’," }, { "type": "UncategorizedText", @@ -531,33 +531,33 @@ }, { "type": "UncategorizedText", - "element_id": "0eab0bd573eb894563f678dcd4b21af8", + "element_id": "b8632182bc1f12dd5b2001d855014004", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i , a start location, ls" + "text": "i , an end time, te" }, { "type": "UncategorizedText", - "element_id": "12017891a1d4e119b40cbf4952a98c9b", + "element_id": "0eab0bd573eb894563f678dcd4b21af8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i , and an end location, le i ," + "text": "i , a start location, ls" }, { "type": "UncategorizedText", - "element_id": "b8632182bc1f12dd5b2001d855014004", + "element_id": "12017891a1d4e119b40cbf4952a98c9b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i , an end time, te" + "text": "i , and an end location, le i ," }, { "type": "UncategorizedText", @@ -591,23 +591,23 @@ }, { "type": "UncategorizedText", - "element_id": "e326e74f4607af7d370e049bc5d9e66a", + "element_id": "8d0736d21edd4e194e5db02347e129c7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "S. Kulkarni et al. / Data in Brief 22 (2019) 484–487" + "text": "486" }, { "type": "UncategorizedText", - "element_id": "8d0736d21edd4e194e5db02347e129c7", + "element_id": "e326e74f4607af7d370e049bc5d9e66a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "486" + "text": "S. Kulkarni et al. / Data in Brief 22 (2019) 484–487" }, { "type": "UncategorizedText", @@ -621,33 +621,33 @@ }, { "type": "UncategorizedText", - "element_id": "af2ea9b1f3593511ded2a7a202fc9779", + "element_id": "f41b22faaa980f33f59eae3874a19ce3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i þδ" + "text": "A trip j can be covered after trip i by the same vehicle, if ts j" }, { "type": "UncategorizedText", - "element_id": "1bca0b1068f467bc18fe15a07bfa74e6", + "element_id": "fa7eead6028158216b4b46d289ab21f1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": ". If le i ls le i j , otherwise, the vehicle may require waiting at le i for the duration of ðts" + "text": "i to ls" }, { "type": "UncategorizedText", - "element_id": "143718a16613779328eee9b3d74b6e3e", + "element_id": "1bca0b1068f467bc18fe15a07bfa74e6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "a ls" + "text": ". If le i ls le i j , otherwise, the vehicle may require waiting at le i for the duration of ðts" }, { "type": "UncategorizedText", @@ -661,13 +661,13 @@ }, { "type": "UncategorizedText", - "element_id": "f41b22faaa980f33f59eae3874a19ce3", + "element_id": "af2ea9b1f3593511ded2a7a202fc9779", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "A trip j can be covered after trip i by the same vehicle, if ts j" + "text": "i þδ" }, { "type": "UncategorizedText", @@ -681,13 +681,13 @@ }, { "type": "UncategorizedText", - "element_id": "fa7eead6028158216b4b46d289ab21f1", + "element_id": "143718a16613779328eee9b3d74b6e3e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i to ls" + "text": "a ls" }, { "type": "UncategorizedText", @@ -709,6 +709,16 @@ }, "text": "the depot." }, + { + "type": "NarrativeText", + "element_id": "e731dc92fddc0512e142bfb2bed62bbf", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 3 + }, + "text": "The dataset also includes a program ‘GenerateInstance.cpp’ that can be used to generate new instances. The program takes three inputs, the number of depots ðmÞ, the number of trips ðnÞ, and the number of instances for each size ðm; nÞ." + }, { "type": "NarrativeText", "element_id": "1c59f2a7ce8a3fa55810df93d58e636e", @@ -769,16 +779,6 @@ }, "text": "." }, - { - "type": "NarrativeText", - "element_id": "e731dc92fddc0512e142bfb2bed62bbf", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 3 - }, - "text": "The dataset also includes a program ‘GenerateInstance.cpp’ that can be used to generate new instances. The program takes three inputs, the number of depots ðmÞ, the number of trips ðnÞ, and the number of instances for each size ðm; nÞ." - }, { "type": "UncategorizedText", "element_id": "5736867eb34c3f0cec0ceabe4505db65", @@ -811,93 +811,93 @@ }, { "type": "UncategorizedText", - "element_id": "d125cfe65ab4cb2d16a7690490605748", + "element_id": "ef43693319ab1036ec2b3c9f09fd1923", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Average number of" + "text": "(8, 1500) (8, 2000) (8, 2500) (8, 3000) (12, 1500) (12, 2000) (12, 2500) (12, 3000) (16, 1500) (16, 2000) (16, 2500) (16, 3000)" }, { "type": "UncategorizedText", - "element_id": "9db0e6acd29863a01533a0eff8ce0437", + "element_id": "d125cfe65ab4cb2d16a7690490605748", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Locations" + "text": "Average number of" }, { "type": "UncategorizedText", - "element_id": "0923bdb0e6ea65dcbaa0a3b52e2ad5b8", + "element_id": "9db0e6acd29863a01533a0eff8ce0437", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Times" + "text": "Locations" }, { "type": "UncategorizedText", - "element_id": "ff25ed0bdb1329e04ac4f11e1d127d40", + "element_id": "4761a1b7b5e09553e6b74a0b5edb7277", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Vehicles" + "text": "568.40 672.80 923.40 977.00 566.00 732.60 875.00 1119.60 581.80 778.00 879.00 1087.20" }, { "type": "UncategorizedText", - "element_id": "ca0aa1db78c07d089347aea892887a60", + "element_id": "0923bdb0e6ea65dcbaa0a3b52e2ad5b8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Possible empty travels" + "text": "Times" }, { "type": "UncategorizedText", - "element_id": "ef43693319ab1036ec2b3c9f09fd1923", + "element_id": "7609557430ac8eaf0442a2d178644db6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "(8, 1500) (8, 2000) (8, 2500) (8, 3000) (12, 1500) (12, 2000) (12, 2500) (12, 3000) (16, 1500) (16, 2000) (16, 2500) (16, 3000)" + "text": "975.20 1048.00 1078.00 1113.20 994.00 1040.60 1081.00 1107.40 985.40 1040.60 1083.20 1101.60" }, { "type": "UncategorizedText", - "element_id": "4761a1b7b5e09553e6b74a0b5edb7277", + "element_id": "ff25ed0bdb1329e04ac4f11e1d127d40", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "568.40 672.80 923.40 977.00 566.00 732.60 875.00 1119.60 581.80 778.00 879.00 1087.20" + "text": "Vehicles" }, { "type": "UncategorizedText", - "element_id": "7609557430ac8eaf0442a2d178644db6", + "element_id": "161dd570f9777f09fcb451430f73e548", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "975.20 1048.00 1078.00 1113.20 994.00 1040.60 1081.00 1107.40 985.40 1040.60 1083.20 1101.60" + "text": "652.20 857.20 1082.40 1272.80 642.00 861.20 1096.00 1286.20 667.80 872.40 1076.40 1284.60" }, { "type": "UncategorizedText", - "element_id": "161dd570f9777f09fcb451430f73e548", + "element_id": "ca0aa1db78c07d089347aea892887a60", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "652.20 857.20 1082.40 1272.80 642.00 861.20 1096.00 1286.20 667.80 872.40 1076.40 1284.60" + "text": "Possible empty travels" }, { "type": "UncategorizedText", @@ -1151,23 +1151,23 @@ }, { "type": "UncategorizedText", - "element_id": "59db06417cc49fb0ed46b010b4a5aa3b", + "element_id": "1f9aae763e91dc58dcdd1ae71ac9f550", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "for the multiple depot vehicle scheduling problem, Transp. Res. Part B Methodol. 118 (2018) 457–487." + "text": "[4] A.S. Pepin, G. Desaulniers, A. Hertz, D. Huisman, A comparison of five heuristics for the multiple depot vehicle scheduling" }, { "type": "UncategorizedText", - "element_id": "1f9aae763e91dc58dcdd1ae71ac9f550", + "element_id": "59db06417cc49fb0ed46b010b4a5aa3b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "[4] A.S. Pepin, G. Desaulniers, A. Hertz, D. Huisman, A comparison of five heuristics for the multiple depot vehicle scheduling" + "text": "for the multiple depot vehicle scheduling problem, Transp. Res. Part B Methodol. 118 (2018) 457–487." }, { "type": "UncategorizedText", diff --git a/test_unstructured_ingest/expected-structured-output/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json b/test_unstructured_ingest/expected-structured-output/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json index 2cb2bb3b55..85cf32f0aa 100644 --- a/test_unstructured_ingest/expected-structured-output/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json @@ -21,23 +21,23 @@ }, { "type": "NarrativeText", - "element_id": "7ffd3b09cb23fc26ab2411d70e53838a", + "element_id": "d16d8a1280ba2acf52f98e9d3c9c2301", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Discussion: Our data confirm previous findings on reduced slow wave density in FEP, and expand them to acute subjects, before any treatment is prescribed. This is in line with available data on diffuse abnormalities of cortico-cortical and cortico-thalamic networks in these patients. Interestingly, our data also offer preliminary evidence that this deficit is specific for SCZ, as it appears to differentiate patients who developed SCZ from those with other diagnoses at follow-up. Given the traveling properties of slow waves, future research should establish their potential as markers of connectivity in SCZ." + "text": "ns; 40 mg/day=3.6%, p<0.05; 80 mg/day=4.9%, p<0.01; 120 mg/day=9.3%, p<0.001, PM dosing group: 20 mg/day=-0.4%, ns; 40 mg/day=2.8%, p<0.05: 80 mg/day=0.2%, ns; 160 mg/day=5.8%, p<0.05). There was no clear dose-dependent trend associated with nausea and RD was similar between AM and PM dosing group (AM dosing group: 20 mg/ day=0.2% ns; 40 mg/day=3.8%, p<0.05; 80 mg/day=3.8%, ns; 120 mg/ day=6.6%, ns, PM dosing group: 20 mg/day=-1.6%, ns; 40 mg/day=-1.7%, ns; 80 mg/day=5.5%, p<0.01; 160 mg/day=2.8%, ns). Discussion: The risk of adverse events in the treatment of schizophrenia with lurasidone can vary depending on the timing of administration. In particular, for akathisia and somnolence, the incidence risks were reduced when lurasidone was administered in PM. Unlike with AM administration, the dose-dependence in the risks of these adverse events were not observed in lurasidone PM administration. The timing of lurasidone administration could be considered in effort to minimize potential adverse events." }, { "type": "NarrativeText", - "element_id": "d16d8a1280ba2acf52f98e9d3c9c2301", + "element_id": "7ffd3b09cb23fc26ab2411d70e53838a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "ns; 40 mg/day=3.6%, p<0.05; 80 mg/day=4.9%, p<0.01; 120 mg/day=9.3%, p<0.001, PM dosing group: 20 mg/day=-0.4%, ns; 40 mg/day=2.8%, p<0.05: 80 mg/day=0.2%, ns; 160 mg/day=5.8%, p<0.05). There was no clear dose-dependent trend associated with nausea and RD was similar between AM and PM dosing group (AM dosing group: 20 mg/ day=0.2% ns; 40 mg/day=3.8%, p<0.05; 80 mg/day=3.8%, ns; 120 mg/ day=6.6%, ns, PM dosing group: 20 mg/day=-1.6%, ns; 40 mg/day=-1.7%, ns; 80 mg/day=5.5%, p<0.01; 160 mg/day=2.8%, ns). Discussion: The risk of adverse events in the treatment of schizophrenia with lurasidone can vary depending on the timing of administration. In particular, for akathisia and somnolence, the incidence risks were reduced when lurasidone was administered in PM. Unlike with AM administration, the dose-dependence in the risks of these adverse events were not observed in lurasidone PM administration. The timing of lurasidone administration could be considered in effort to minimize potential adverse events." + "text": "Discussion: Our data confirm previous findings on reduced slow wave density in FEP, and expand them to acute subjects, before any treatment is prescribed. This is in line with available data on diffuse abnormalities of cortico-cortical and cortico-thalamic networks in these patients. Interestingly, our data also offer preliminary evidence that this deficit is specific for SCZ, as it appears to differentiate patients who developed SCZ from those with other diagnoses at follow-up. Given the traveling properties of slow waves, future research should establish their potential as markers of connectivity in SCZ." }, { "type": "Title", @@ -50,54 +50,54 @@ "text": "S7. INVESTIGATING THE LINK BETWEEN THE PERIPHERAL ENDOCANNABINOID SYSTEM AND CENTRAL GLUTAMATERGIC NEUROTRANSMISSION IN EARLY PSYCHOSIS: A 7T-MRS STUDY" }, { - "type": "NarrativeText", - "element_id": "d981d6dfaa8794c0bb733db0965b2831", + "type": "Title", + "element_id": "0302f9e0f412cb4c63f13818e571c25c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Amedeo Minichino*1, Beata Godlewska1, Philip Cowen1, Philip Burnet1, Belinda Lennox1 1University of Oxford" + "text": "S6. SLEEP ENDOPHENOTYPES OF SCHIZOPHRENIA: A HIGH-DENSITY EEG STUDY IN DRUG-NAÏVE, FIRST EPISODE PSYCHOSIS PATIENTS" }, { - "type": "Title", - "element_id": "0302f9e0f412cb4c63f13818e571c25c", + "type": "UncategorizedText", + "element_id": "18b532c1eceea81650bc4925582c44c1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "S6. SLEEP ENDOPHENOTYPES OF SCHIZOPHRENIA: A HIGH-DENSITY EEG STUDY IN DRUG-NAÏVE, FIRST EPISODE PSYCHOSIS PATIENTS" + "text": "Anna Castelnovo1, Cecilia Casetta2, Francesco Donati3, Renata del Giudice3, Caroline Zangani3, Simone Sarasso3, Armando D’Agostino*3 1Faculty of Biomedical Sciences, Università della Svizzera Italiana, Switzerland; 2Institute of Psychiatry, Psychology and Neuroscience, King’s College London, England; 3Università degli Studi di Milano, Italy" }, { - "type": "NarrativeText", - "element_id": "6164e852cb79f9408e833e350240ac5c", + "type": "UncategorizedText", + "element_id": "8aa10e9d14227aadb36fe13b1086b431", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Background: Meta-analytic evidence showed increased levels of periph- eral endocannabinoid metabolites in psychotic illness. Alterations in the endocannabinoid system are believed to compromise glutamate and do- pamine transmission, which play a central role in pathophysiological models of psychosis. I will present preliminary data from an ongoing high-field proton magnetic resonance spectroscopy (MRS) study aimed at investigating the association between peripheral levels of endocannabinoid system metabolites and central glutamate metabolism in individuals at their first non-affective psychotic episode (NA-FEP) and healthy controls. Methods: We expect to recruit 17 NA-FEP and 20 healthy controls by January 2020. Currently, we recruited 12 NA-FEP and 18 healthy controls from two different research facilities (Imperial College London and University of Oxford) as part of a cross-sectional study. Participants un- derwent MRS scanning at 7-T with voxels placed in right dorsolateral prefrontal cortex (right-DLPFC), anterior cingulate cortex (ACC), and oc- cipital cortex. Neuro-metabolites will be calculated using the unsuppressed water signal as reference. Endocannabinoid metabolites were quantified from serum samples, collected during the same imaging session. Results: Analyses are ongoing. Based on previous evidence, expected findings are: (i) reduced glutamate levels in the ACC and right-DLPFC of NA-FEP compared to controls; (ii) increased peripheral endocannabinoid metabolites in NA-FEP compared to controls; and (iii) inverse association between peripheral endocannabinoid metabolites and glutamate levels in ACC and right-DLPFC in NA-FEP Discussion: This study will help clarifying the contribution of peripheral endocannabinoid system to central brain mechanisms of key relevance for psychotic illness. It will also add further evidence on the limited literature on high-resolution characterisation of brain metabolites in early psychosis. Strengths of the study include: (i) use of high-field MRS, which allows the estimation of glutamate-related compounds at higher precision than at lower field strength; (ii) reduced heterogeneity of the clinical sample (only male and NA-FEP). Limitations: small sample size and cross-sectional design." + "text": "Background: Slow waves, the hallmark of the deep nonrapid eye move- ment sleep electroencephalogram (EEG), are critical for restorative sleep and brain plasticity. They arise from the synchronous depolarization and hyperpolarization of millions of cortical neurons and their proper gen- eration and propagation relies upon the integrity of widespread cortico- thalamic networks. Slow wave abnormalities have been reported in patient with Schizophrenia, although with partially contradictory results, probably related to antipsychotic and sedative medications. Recently, their presence and delineation, have been convincingly shown in first-episode psychosis patients (FEP). However, clear evidence of this biomarker at the onset of the disease, prior to any psychopharmacological intervention, remains limited. Moreover, no attempt has been made to elucidate the prognostic meaning of this finding. Methods: We collected whole night sleep high–density electroencephalog- raphy recordings (64-channel BrainAmp, Brain Products GmbH, Gilching, Germany) in 20 drug-naive FEP patients and 20 healthy control subjects (HC). Several clinical psychometric scales as well as neurocognitive tests were administered to all subjects in order to better define psychopatholog- ical status and vulnerability. EEG slow wave activity (SWA, spectral power between 1 and 4 Hz) and several slow wave parameters were computed at each electrode location, including density and amplitude, at each electrode location. Along with a group analysis between FEP and HC, a subgroup analysis was also computed between patients who showed a progression of symptoms to full-blown Schizophrenia (SCZ, n = 10) over the next 12-month follow-up and those who did not (OTH, n = 10). Results: Sleep macro-architecture was globally preserved in FEP patients. SWA (1–4 Hz) was lower in FEP compared to HC but this difference didn’t reach statistical significance. Slow wave density was decreased in FEP compared to HC, with a significance that survived multiple comparison correction over a large fronto-central cluster. Mean amplitude was pre- served. At the subgroup analysis, these results were largely driven by the subgroup of patients with a confirmed diagnosis of SCZ at a 12-month fol- low-up. Indeed, no difference could be found between OTH and HC, while a strong significance was still evident between SCZ and HC." }, { - "type": "UncategorizedText", - "element_id": "18b532c1eceea81650bc4925582c44c1", + "type": "NarrativeText", + "element_id": "d981d6dfaa8794c0bb733db0965b2831", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Anna Castelnovo1, Cecilia Casetta2, Francesco Donati3, Renata del Giudice3, Caroline Zangani3, Simone Sarasso3, Armando D’Agostino*3 1Faculty of Biomedical Sciences, Università della Svizzera Italiana, Switzerland; 2Institute of Psychiatry, Psychology and Neuroscience, King’s College London, England; 3Università degli Studi di Milano, Italy" + "text": "Amedeo Minichino*1, Beata Godlewska1, Philip Cowen1, Philip Burnet1, Belinda Lennox1 1University of Oxford" }, { - "type": "UncategorizedText", - "element_id": "8aa10e9d14227aadb36fe13b1086b431", + "type": "NarrativeText", + "element_id": "6164e852cb79f9408e833e350240ac5c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Background: Slow waves, the hallmark of the deep nonrapid eye move- ment sleep electroencephalogram (EEG), are critical for restorative sleep and brain plasticity. They arise from the synchronous depolarization and hyperpolarization of millions of cortical neurons and their proper gen- eration and propagation relies upon the integrity of widespread cortico- thalamic networks. Slow wave abnormalities have been reported in patient with Schizophrenia, although with partially contradictory results, probably related to antipsychotic and sedative medications. Recently, their presence and delineation, have been convincingly shown in first-episode psychosis patients (FEP). However, clear evidence of this biomarker at the onset of the disease, prior to any psychopharmacological intervention, remains limited. Moreover, no attempt has been made to elucidate the prognostic meaning of this finding. Methods: We collected whole night sleep high–density electroencephalog- raphy recordings (64-channel BrainAmp, Brain Products GmbH, Gilching, Germany) in 20 drug-naive FEP patients and 20 healthy control subjects (HC). Several clinical psychometric scales as well as neurocognitive tests were administered to all subjects in order to better define psychopatholog- ical status and vulnerability. EEG slow wave activity (SWA, spectral power between 1 and 4 Hz) and several slow wave parameters were computed at each electrode location, including density and amplitude, at each electrode location. Along with a group analysis between FEP and HC, a subgroup analysis was also computed between patients who showed a progression of symptoms to full-blown Schizophrenia (SCZ, n = 10) over the next 12-month follow-up and those who did not (OTH, n = 10). Results: Sleep macro-architecture was globally preserved in FEP patients. SWA (1–4 Hz) was lower in FEP compared to HC but this difference didn’t reach statistical significance. Slow wave density was decreased in FEP compared to HC, with a significance that survived multiple comparison correction over a large fronto-central cluster. Mean amplitude was pre- served. At the subgroup analysis, these results were largely driven by the subgroup of patients with a confirmed diagnosis of SCZ at a 12-month fol- low-up. Indeed, no difference could be found between OTH and HC, while a strong significance was still evident between SCZ and HC." + "text": "Background: Meta-analytic evidence showed increased levels of periph- eral endocannabinoid metabolites in psychotic illness. Alterations in the endocannabinoid system are believed to compromise glutamate and do- pamine transmission, which play a central role in pathophysiological models of psychosis. I will present preliminary data from an ongoing high-field proton magnetic resonance spectroscopy (MRS) study aimed at investigating the association between peripheral levels of endocannabinoid system metabolites and central glutamate metabolism in individuals at their first non-affective psychotic episode (NA-FEP) and healthy controls. Methods: We expect to recruit 17 NA-FEP and 20 healthy controls by January 2020. Currently, we recruited 12 NA-FEP and 18 healthy controls from two different research facilities (Imperial College London and University of Oxford) as part of a cross-sectional study. Participants un- derwent MRS scanning at 7-T with voxels placed in right dorsolateral prefrontal cortex (right-DLPFC), anterior cingulate cortex (ACC), and oc- cipital cortex. Neuro-metabolites will be calculated using the unsuppressed water signal as reference. Endocannabinoid metabolites were quantified from serum samples, collected during the same imaging session. Results: Analyses are ongoing. Based on previous evidence, expected findings are: (i) reduced glutamate levels in the ACC and right-DLPFC of NA-FEP compared to controls; (ii) increased peripheral endocannabinoid metabolites in NA-FEP compared to controls; and (iii) inverse association between peripheral endocannabinoid metabolites and glutamate levels in ACC and right-DLPFC in NA-FEP Discussion: This study will help clarifying the contribution of peripheral endocannabinoid system to central brain mechanisms of key relevance for psychotic illness. It will also add further evidence on the limited literature on high-resolution characterisation of brain metabolites in early psychosis. Strengths of the study include: (i) use of high-field MRS, which allows the estimation of glutamate-related compounds at higher precision than at lower field strength; (ii) reduced heterogeneity of the clinical sample (only male and NA-FEP). Limitations: small sample size and cross-sectional design." }, { "type": "Title", diff --git a/test_unstructured_ingest/expected-structured-output/local-single-file-with-pdf-infer-table-structure/layout-parser-paper.pdf.json b/test_unstructured_ingest/expected-structured-output/local-single-file-with-pdf-infer-table-structure/layout-parser-paper.pdf.json index 4c78276585..044118618f 100644 --- a/test_unstructured_ingest/expected-structured-output/local-single-file-with-pdf-infer-table-structure/layout-parser-paper.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/local-single-file-with-pdf-infer-table-structure/layout-parser-paper.pdf.json @@ -20,134 +20,134 @@ "text": "Zejiang Shen1 ((cid:0)), Ruochen Zhang2, Melissa Dell3, Benjamin Charles Germain Lee4, Jacob Carlson3, and Weining Li5" }, { - "type": "ListItem", - "element_id": "d598892f792aa3f81bde483737ac163e", + "type": "UncategorizedText", + "element_id": "7dce5432959ba3ffb1edad16bc3f458c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Allen Institute for AI shannons@allenai.org" + "text": "1 2 0 2" }, { - "type": "ListItem", - "element_id": "c44dd169d4120fc474358e959bc32f27", + "type": "UncategorizedText", + "element_id": "c8d21c806367081195dd372b58005d48", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Brown University ruochen zhang@brown.edu" + "text": "n u J" }, { - "type": "ListItem", - "element_id": "69ce85202ad89819bf6a6687c34c04a0", + "type": "UncategorizedText", + "element_id": "a6e2b7a040683432de03a18fd8a1939a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Harvard University {melissadell,jacob carlson}@fas.harvard.edu" + "text": "1 2" }, { - "type": "ListItem", - "element_id": "ee43ace21caffc7f3e421e0d25282863", + "type": "UncategorizedText", + "element_id": "f9416e09f78ba316c032568213b855ee", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "University of Washington bcgl@cs.washington.edu" + "text": "]" }, { - "type": "ListItem", - "element_id": "91e84c77f84bea17e45f12fe8d612afa", + "type": "UncategorizedText", + "element_id": "20f7b3c9b9ca29dbbf5c1975fb8894a9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "University of Waterloo w" + "text": "V C . s c [" }, { - "type": "ListItem", - "element_id": "a02bbc7d83b04c67fcac3ae66b21b824", + "type": "UncategorizedText", + "element_id": "12529cdcfd90d0bf95ff502804e61a16", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "li@uwaterloo.ca" + "text": "2 v 8 4 3 5 1 . 3 0 1 2 : v i X r a" }, { - "type": "UncategorizedText", - "element_id": "7dce5432959ba3ffb1edad16bc3f458c", + "type": "ListItem", + "element_id": "a02bbc7d83b04c67fcac3ae66b21b824", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "1 2 0 2" + "text": "li@uwaterloo.ca" }, { - "type": "UncategorizedText", - "element_id": "c8d21c806367081195dd372b58005d48", + "type": "ListItem", + "element_id": "91e84c77f84bea17e45f12fe8d612afa", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "n u J" + "text": "University of Waterloo w" }, { - "type": "UncategorizedText", - "element_id": "a6e2b7a040683432de03a18fd8a1939a", + "type": "ListItem", + "element_id": "ee43ace21caffc7f3e421e0d25282863", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "1 2" + "text": "University of Washington bcgl@cs.washington.edu" }, { - "type": "UncategorizedText", - "element_id": "f9416e09f78ba316c032568213b855ee", + "type": "ListItem", + "element_id": "69ce85202ad89819bf6a6687c34c04a0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "]" + "text": "Harvard University {melissadell,jacob carlson}@fas.harvard.edu" }, { - "type": "UncategorizedText", - "element_id": "20f7b3c9b9ca29dbbf5c1975fb8894a9", + "type": "ListItem", + "element_id": "c44dd169d4120fc474358e959bc32f27", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "V C . s c [" + "text": "Brown University ruochen zhang@brown.edu" }, { - "type": "NarrativeText", - "element_id": "be90d2640470e975e3402d19ba2c66cf", + "type": "ListItem", + "element_id": "d598892f792aa3f81bde483737ac163e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Abstract. Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for further investigation. However, various factors like loosely organized codebases and sophisticated model configurations complicate the easy reuse of im- portant innovations by a wide audience. Though there have been on-going efforts to improve reusability and simplify deep learning (DL) model development in disciplines like natural language processing and computer vision, none of them are optimized for challenges in the domain of DIA. This represents a major gap in the existing toolkit, as DIA is central to academic research across a wide range of disciplines in the social sciences and humanities. This paper introduces LayoutParser, an open-source library for streamlining the usage of DL in DIA research and applica- tions. The core LayoutParser library comes with a set of simple and intuitive interfaces for applying and customizing DL models for layout de- tection, character recognition, and many other document processing tasks. To promote extensibility, LayoutParser also incorporates a community platform for sharing both pre-trained models and full document digiti- zation pipelines. We demonstrate that LayoutParser is helpful for both lightweight and large-scale digitization pipelines in real-word use cases. The library is publicly available at https://layout-parser.github.io." + "text": "Allen Institute for AI shannons@allenai.org" }, { - "type": "UncategorizedText", - "element_id": "12529cdcfd90d0bf95ff502804e61a16", + "type": "NarrativeText", + "element_id": "be90d2640470e975e3402d19ba2c66cf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "2 v 8 4 3 5 1 . 3 0 1 2 : v i X r a" + "text": "Abstract. Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for further investigation. However, various factors like loosely organized codebases and sophisticated model configurations complicate the easy reuse of im- portant innovations by a wide audience. Though there have been on-going efforts to improve reusability and simplify deep learning (DL) model development in disciplines like natural language processing and computer vision, none of them are optimized for challenges in the domain of DIA. This represents a major gap in the existing toolkit, as DIA is central to academic research across a wide range of disciplines in the social sciences and humanities. This paper introduces LayoutParser, an open-source library for streamlining the usage of DL in DIA research and applica- tions. The core LayoutParser library comes with a set of simple and intuitive interfaces for applying and customizing DL models for layout de- tection, character recognition, and many other document processing tasks. To promote extensibility, LayoutParser also incorporates a community platform for sharing both pre-trained models and full document digiti- zation pipelines. We demonstrate that LayoutParser is helpful for both lightweight and large-scale digitization pipelines in real-word use cases. The library is publicly available at https://layout-parser.github.io." }, { "type": "NarrativeText", @@ -160,24 +160,24 @@ "text": "Keywords: Document Image Analysis · Deep Learning · Layout Analysis · Character Recognition · Open Source library · Toolkit." }, { - "type": "Title", - "element_id": "3fa53fc0dab8ef96d05d8fd4c7e41b49", + "type": "UncategorizedText", + "element_id": "4355a46b19d348dc2f57c046f8ef63d4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Introduction" + "text": "1" }, { - "type": "UncategorizedText", - "element_id": "4355a46b19d348dc2f57c046f8ef63d4", + "type": "Title", + "element_id": "3fa53fc0dab8ef96d05d8fd4c7e41b49", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "1" + "text": "Introduction" }, { "type": "NarrativeText", @@ -351,23 +351,23 @@ }, { "type": "NarrativeText", - "element_id": "74a7758f83612467af8eea9d20e4a6f7", + "element_id": "9b8fc4816306f4f1b31874d53134979b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "that require precision, efficiency, and robustness, as well as simple and light- weight document processing tasks focusing on efficacy and flexibility (Section 5). LayoutParser is being actively maintained, and support for more deep learning models and novel methods in text-based layout analysis methods [37, 34] is planned." + "text": "The rest of the paper is organized as follows. Section 2 provides an overview of related work. The core LayoutParser library, DL Model Zoo, and customized model training are described in Section 3, and the DL model hub and commu- nity platform are detailed in Section 4. Section 5 shows two examples of how LayoutParser can be used in practical DIA projects, and Section 6 concludes." }, { "type": "NarrativeText", - "element_id": "9b8fc4816306f4f1b31874d53134979b", + "element_id": "74a7758f83612467af8eea9d20e4a6f7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "The rest of the paper is organized as follows. Section 2 provides an overview of related work. The core LayoutParser library, DL Model Zoo, and customized model training are described in Section 3, and the DL model hub and commu- nity platform are detailed in Section 4. Section 5 shows two examples of how LayoutParser can be used in practical DIA projects, and Section 6 concludes." + "text": "that require precision, efficiency, and robustness, as well as simple and light- weight document processing tasks focusing on efficacy and flexibility (Section 5). LayoutParser is being actively maintained, and support for more deep learning models and novel methods in text-based layout analysis methods [37, 34] is planned." }, { "type": "Title", @@ -411,153 +411,153 @@ }, { "type": "ListItem", - "element_id": "27494431886c5be0e1b0dbeb2831a1e6", + "element_id": "f6adbb1b29c00a0317d87307ea7349c0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "The number shown is obtained by specifying the search type as ‘code’." + "text": "https://github.com/Paddl" }, { "type": "ListItem", - "element_id": "193e03893373b61e7354231571171b6f", + "element_id": "c13539d1568999137c4e0354795cd37b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "https://ocr-d.de/en/about" + "text": "CR" }, { "type": "ListItem", - "element_id": "a180bff913a0059538fe3609d9db6832", + "element_id": "c9a7576974bf76f87205a547952012b9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "https://github.com/Bo" + "text": "I/Eas" }, { "type": "ListItem", - "element_id": "3be8a9f080762eb3b89459c83b9dc0cc", + "element_id": "f12bcd1c4c95f968487ef1d92f721777", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "d/Documen" + "text": "https://github.com/Jaide" }, { "type": "ListItem", - "element_id": "c84915bf4d12c1d1794529a2197c8f7e", + "element_id": "0c4475e4ef576fc3ba91edb83ac90529", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "ayou" + "text": "/detectron" }, { "type": "ListItem", - "element_id": "96811996068f19e87f4fc6944d2534c0", + "element_id": "85932d11fa05437c5aca785378fe8b88", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "nalysis" + "text": "https://github.com/hpanwar" }, { "type": "ListItem", - "element_id": "9b41ceaccf9f13d73692f2e1f5ec87ca", + "element_id": "fcec4cb3f8a40c9c97f67564ef7b01cf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "https://github.com/leonlulu/Dee" + "text": "ayout" }, { "type": "ListItem", - "element_id": "fcec4cb3f8a40c9c97f67564ef7b01cf", + "element_id": "3be8a9f080762eb3b89459c83b9dc0cc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "ayout" + "text": "d/Documen" }, { "type": "ListItem", - "element_id": "85932d11fa05437c5aca785378fe8b88", + "element_id": "96811996068f19e87f4fc6944d2534c0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "https://github.com/hpanwar" + "text": "nalysis" }, { "type": "ListItem", - "element_id": "0c4475e4ef576fc3ba91edb83ac90529", + "element_id": "c84915bf4d12c1d1794529a2197c8f7e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "/detectron" + "text": "ayou" }, { "type": "ListItem", - "element_id": "f12bcd1c4c95f968487ef1d92f721777", + "element_id": "a52d4e55ffcecbb2b7e10950d6e3d2ff", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "https://github.com/Jaide" + "text": "addle/Paddl" }, { "type": "ListItem", - "element_id": "c9a7576974bf76f87205a547952012b9", + "element_id": "a180bff913a0059538fe3609d9db6832", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "I/Eas" + "text": "https://github.com/Bo" }, { "type": "ListItem", - "element_id": "c13539d1568999137c4e0354795cd37b", + "element_id": "193e03893373b61e7354231571171b6f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "CR" + "text": "https://ocr-d.de/en/about" }, { "type": "ListItem", - "element_id": "f6adbb1b29c00a0317d87307ea7349c0", + "element_id": "27494431886c5be0e1b0dbeb2831a1e6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "https://github.com/Paddl" + "text": "The number shown is obtained by specifying the search type as ‘code’." }, { "type": "ListItem", - "element_id": "a52d4e55ffcecbb2b7e10950d6e3d2ff", + "element_id": "9b41ceaccf9f13d73692f2e1f5ec87ca", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "addle/Paddl" + "text": "https://github.com/leonlulu/Dee" }, { "type": "ListItem", @@ -669,16 +669,6 @@ }, "text": "5" }, - { - "type": "NarrativeText", - "element_id": "b51f99cb953082a922ba43c09d4492b3", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 5 - }, - "text": "Table 1: Current layout detection models in the LayoutParser model zoo" - }, { "type": "Table", "element_id": "34923b77ca76e1808956ade5e766f7c2", @@ -692,13 +682,23 @@ }, { "type": "UncategorizedText", - "element_id": "654021138cc8eb1409b192c9c6bc9cad", + "element_id": "d994f2b2f63ea8768ac77b181d3621f6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "Base Model1 Large Model Notes" + "text": "PubLayNet [38] PRImA [3] Newspaper [17] TableBank [18] HJDataset [31]" + }, + { + "type": "NarrativeText", + "element_id": "b51f99cb953082a922ba43c09d4492b3", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 5 + }, + "text": "Table 1: Current layout detection models in the LayoutParser model zoo" }, { "type": "UncategorizedText", @@ -712,13 +712,13 @@ }, { "type": "UncategorizedText", - "element_id": "d994f2b2f63ea8768ac77b181d3621f6", + "element_id": "654021138cc8eb1409b192c9c6bc9cad", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "PubLayNet [38] PRImA [3] Newspaper [17] TableBank [18] HJDataset [31]" + "text": "Base Model1 Large Model Notes" }, { "type": "UncategorizedText", @@ -802,23 +802,23 @@ }, { "type": "UncategorizedText", - "element_id": "4b27636ffb1723123a6cfbf67a2aa183", + "element_id": "ac9c43a46f1221e9cc7611e910c88b58", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "\" lp :// PubLayNet / f as t er _ r c nn _ R _ 50 _ F P N_ 3 x / config \" )" + "text": "4 5 layout = model . detect ( image )" }, { "type": "UncategorizedText", - "element_id": "ac9c43a46f1221e9cc7611e910c88b58", + "element_id": "4b27636ffb1723123a6cfbf67a2aa183", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "4 5 layout = model . detect ( image )" + "text": "\" lp :// PubLayNet / f as t er _ r c nn _ R _ 50 _ F P N_ 3 x / config \" )" }, { "type": "NarrativeText", @@ -1073,193 +1073,193 @@ }, { "type": "UncategorizedText", - "element_id": "88f06b9b69e717a8a691e10387779bcf", + "element_id": "bc47d0cd9d800d84cd9aefa2d9ec63ec", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Operation Name" + "text": "block1.condition on(block2)" }, { "type": "UncategorizedText", - "element_id": "c43500c63a83847bc5dd317182f0eaeb", + "element_id": "1e09f3ee1bda1e38a11dbc80108923f1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Description" + "text": "block1.relative to(block2)" }, { "type": "UncategorizedText", - "element_id": "4606a3cb33e7e6857f77dda2c1daf535", + "element_id": "fdbeffff8c43aaf3bbeb4791175c4e43", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block.pad(top, bottom, right, left) Enlarge the current block according to the input" + "text": "block1.union(block2)" }, { "type": "UncategorizedText", - "element_id": "97f87287f36dbf6c636a3017ae0879fb", + "element_id": "517de49526055a51ab0e815fe66a5c73", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Scale the current block given the ratio in x and y direction" + "text": "block1.intersect(block2)" }, { "type": "UncategorizedText", - "element_id": "7cd6132d1ae515ab6d484f1b74e1c7e6", + "element_id": "06c072cc8c8ed04ca343b16beb144048", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block.scale(fx, fy)" + "text": "block.shift(dx, dy)" }, { "type": "UncategorizedText", - "element_id": "25dc86fe689dee9f82609342e44e5ce3", + "element_id": "9281c2571853bd5e586a12067782746d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Move the current block with the shift distances in x and y direction" + "text": "block1.is in(block2)" }, { "type": "UncategorizedText", - "element_id": "06c072cc8c8ed04ca343b16beb144048", + "element_id": "7cd6132d1ae515ab6d484f1b74e1c7e6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block.shift(dx, dy)" + "text": "block.scale(fx, fy)" }, { "type": "UncategorizedText", - "element_id": "4e5821785ee2be3e8c853010a6ad0b76", + "element_id": "4606a3cb33e7e6857f77dda2c1daf535", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Whether block1 is inside of block2" + "text": "block.pad(top, bottom, right, left) Enlarge the current block according to the input" }, { "type": "UncategorizedText", - "element_id": "9281c2571853bd5e586a12067782746d", + "element_id": "88f06b9b69e717a8a691e10387779bcf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block1.is in(block2)" + "text": "Operation Name" }, { "type": "UncategorizedText", - "element_id": "6afa487379762db34fc58d243c408566", + "element_id": "e2d920d1b163490b690e3730fda41064", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Return the intersection region of block1 and block2. Coordinate type to be determined based on the inputs." + "text": "block.crop image(image)" }, { "type": "UncategorizedText", - "element_id": "517de49526055a51ab0e815fe66a5c73", + "element_id": "4e5821785ee2be3e8c853010a6ad0b76", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block1.intersect(block2)" + "text": "Whether block1 is inside of block2" }, { "type": "UncategorizedText", - "element_id": "8bdb5b868be61ec346e052b25ed4022a", + "element_id": "9ba6cbc77549790313b84b62a781a1f9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Return the union region of block1 and block2. Coordinate type to be determined based on the inputs." + "text": "Obtain the image segments in the block region" }, { "type": "UncategorizedText", - "element_id": "fdbeffff8c43aaf3bbeb4791175c4e43", + "element_id": "6afa487379762db34fc58d243c408566", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block1.union(block2)" + "text": "Return the intersection region of block1 and block2. Coordinate type to be determined based on the inputs." }, { "type": "UncategorizedText", - "element_id": "46e8fb35b2888c35a00033faaa4851d9", + "element_id": "97f87287f36dbf6c636a3017ae0879fb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Convert the absolute coordinates of block1 to relative coordinates to block2" + "text": "Scale the current block given the ratio in x and y direction" }, { "type": "UncategorizedText", - "element_id": "1e09f3ee1bda1e38a11dbc80108923f1", + "element_id": "8bdb5b868be61ec346e052b25ed4022a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block1.relative to(block2)" + "text": "Return the union region of block1 and block2. Coordinate type to be determined based on the inputs." }, { "type": "UncategorizedText", - "element_id": "b8a944f0af3a0a8cfc854d5c9b186900", + "element_id": "46e8fb35b2888c35a00033faaa4851d9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Calculate the absolute coordinates of block1 given the canvas block2’s absolute coordinates" + "text": "Convert the absolute coordinates of block1 to relative coordinates to block2" }, { "type": "UncategorizedText", - "element_id": "bc47d0cd9d800d84cd9aefa2d9ec63ec", + "element_id": "c43500c63a83847bc5dd317182f0eaeb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block1.condition on(block2)" + "text": "Description" }, { "type": "UncategorizedText", - "element_id": "9ba6cbc77549790313b84b62a781a1f9", + "element_id": "b8a944f0af3a0a8cfc854d5c9b186900", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Obtain the image segments in the block region" + "text": "Calculate the absolute coordinates of block1 given the canvas block2’s absolute coordinates" }, { "type": "UncategorizedText", - "element_id": "e2d920d1b163490b690e3730fda41064", + "element_id": "25dc86fe689dee9f82609342e44e5ce3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "block.crop image(image)" + "text": "Move the current block with the shift distances in x and y direction" }, { "type": "Title", @@ -1402,34 +1402,34 @@ "text": "After the training dataset is curated, LayoutParser supports different modes for training the layout models. Fine-tuning can be used for training models on a small newly-labeled dataset by initializing the model with existing pre-trained weights. Training from scratch can be helpful when the source dataset and target are significantly different and a large training set is available. However, as suggested in Studer et al.’s work[33], loading pre-trained weights on large-scale datasets like ImageNet [5], even from totally different domains, can still boost model performance. Through the integrated API provided by LayoutParser, users can easily compare model performances on the benchmark datasets." }, { - "type": "UncategorizedText", - "element_id": "917df3320d778ddbaa5c5c7742bc4046", + "type": "FigureCaption", + "element_id": "2680b3c7a55754a3ba2738cb3d9d5e8b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "10" + "text": "et Intra-column reading order Token Categories tie (Adress 2) tee (NE sumber Variable HEE company type Column Categories (J tite we) adaress —_ (7) section Header by ‘e * Column reading order a a (a) Illustration of the original Japanese Maximum Allowed Height BRE B>e EER eR (b) Illustration of the recreated document with dense text structure for better OCR performance" }, { "type": "UncategorizedText", - "element_id": "22364b7a1d2b35282b360d61ae08e2b9", + "element_id": "917df3320d778ddbaa5c5c7742bc4046", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "Z. Shen et al." + "text": "10" }, { - "type": "FigureCaption", - "element_id": "2680b3c7a55754a3ba2738cb3d9d5e8b", + "type": "UncategorizedText", + "element_id": "22364b7a1d2b35282b360d61ae08e2b9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "et Intra-column reading order Token Categories tie (Adress 2) tee (NE sumber Variable HEE company type Column Categories (J tite we) adaress —_ (7) section Header by ‘e * Column reading order a a (a) Illustration of the original Japanese Maximum Allowed Height BRE B>e EER eR (b) Illustration of the recreated document with dense text structure for better OCR performance" + "text": "Z. Shen et al." }, { "type": "NarrativeText", @@ -1533,43 +1533,43 @@ }, { "type": "UncategorizedText", - "element_id": "a5a6fe2f9e40a8e2b2fe290d51094b4d", + "element_id": "fa19ab2536cbbb48c09de29fdebd52bd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "The digitization of historical documents can unlock valuable data that can shed light on many important social, economic, and historical questions. Yet due to scan noises, page wearing, and the prevalence of complicated layout structures, ob- taining a structured representation of historical document scans is often extremely complicated. In this example, LayoutParser was used to develop a comprehensive pipeline, shown in Figure 5, to gener- ate high-quality structured data from historical Japanese firm financial ta- bles with complicated layouts. The pipeline applies two layout models to identify different levels of document structures and two customized OCR engines for optimized character recog- nition accuracy." + "text": "As shown in Figure 4 (a), the document contains columns of text written vertically 15, a common style in Japanese. Due to scanning noise and archaic printing technology, the columns can be skewed or have vari- able widths, and hence cannot be eas- ily identified via rule-based methods. Within each column, words are sepa- rated by white spaces of variable size, and the vertical positions of objects can be an indicator of their layout type." }, { - "type": "FigureCaption", - "element_id": "b33b2bc3b9c416673c7f74c6a00c49d8", + "type": "UncategorizedText", + "element_id": "a5a6fe2f9e40a8e2b2fe290d51094b4d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "(spe peepee, ‘Active Learning Layout Annotate Layout Dataset | + ‘Annotation Toolkit ¥ a Deep Leaming Layout Model Training & Inference, ¥ ; Handy Data Structures & Post-processing El Apis for Layout Det a LAR ror tye eats) 4 Text Recognition | <—— Default ane Customized ¥ ee Layout Structure Visualization & Export | <—— | visualization & Storage The Japanese Document Helpful LayoutParser Digitization Pipeline Modules" + "text": "The digitization of historical documents can unlock valuable data that can shed light on many important social, economic, and historical questions. Yet due to scan noises, page wearing, and the prevalence of complicated layout structures, ob- taining a structured representation of historical document scans is often extremely complicated. In this example, LayoutParser was used to develop a comprehensive pipeline, shown in Figure 5, to gener- ate high-quality structured data from historical Japanese firm financial ta- bles with complicated layouts. The pipeline applies two layout models to identify different levels of document structures and two customized OCR engines for optimized character recog- nition accuracy." }, { "type": "UncategorizedText", - "element_id": "fa19ab2536cbbb48c09de29fdebd52bd", + "element_id": "3cbd8234ac0c6d29feb24e6202144aa8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "As shown in Figure 4 (a), the document contains columns of text written vertically 15, a common style in Japanese. Due to scanning noise and archaic printing technology, the columns can be skewed or have vari- able widths, and hence cannot be eas- ily identified via rule-based methods. Within each column, words are sepa- rated by white spaces of variable size, and the vertical positions of objects can be an indicator of their layout type." + "text": "Fig. 5: Illustration of how LayoutParser helps with the historical document digi- tization pipeline." }, { - "type": "UncategorizedText", - "element_id": "3cbd8234ac0c6d29feb24e6202144aa8", + "type": "FigureCaption", + "element_id": "b33b2bc3b9c416673c7f74c6a00c49d8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Fig. 5: Illustration of how LayoutParser helps with the historical document digi- tization pipeline." + "text": "(spe peepee, ‘Active Learning Layout Annotate Layout Dataset | + ‘Annotation Toolkit ¥ a Deep Leaming Layout Model Training & Inference, ¥ ; Handy Data Structures & Post-processing El Apis for Layout Det a LAR ror tye eats) 4 Text Recognition | <—— Default ane Customized ¥ ee Layout Structure Visualization & Export | <—— | visualization & Storage The Japanese Document Helpful LayoutParser Digitization Pipeline Modules" }, { "type": "UncategorizedText", @@ -1592,44 +1592,44 @@ "text": "segmentation discussion and refer readers to the source code when available." }, { - "type": "Title", - "element_id": "22364b7a1d2b35282b360d61ae08e2b9", + "type": "UncategorizedText", + "element_id": "a1fb50e6c86fae1679ef3351296fd671", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "Z. Shen et al." + "text": "12" }, { - "type": "UncategorizedText", - "element_id": "a1fb50e6c86fae1679ef3351296fd671", + "type": "Title", + "element_id": "22364b7a1d2b35282b360d61ae08e2b9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "12" + "text": "Z. Shen et al." }, { - "type": "UncategorizedText", - "element_id": "7174760d4c8d9b7b13da3918015312dc", + "type": "NarrativeText", + "element_id": "9b51c55d2dd4ffd289138fc4f66e11e6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "To decipher the complicated layout" + "text": "structure, two object detection models have been trained to recognize individual columns and tokens, respectively. A small training set (400 images with approxi- mately 100 annotations each) is curated via the active learning based annotation tool [32] in LayoutParser. The models learn to identify both the categories and regions for each token or column via their distinct visual features. The layout data structure enables easy grouping of the tokens within each column, and rearranging columns to achieve the correct reading orders based on the horizontal position. Errors are identified and rectified via checking the consistency of the model predictions. Therefore, though trained on a small dataset, the pipeline achieves a high level of layout detection accuracy: it achieves a 96.97 AP [19] score across 5 categories for the column detection model, and a 89.23 AP across 4 categories for the token detection model." }, { - "type": "NarrativeText", - "element_id": "9b51c55d2dd4ffd289138fc4f66e11e6", + "type": "UncategorizedText", + "element_id": "7174760d4c8d9b7b13da3918015312dc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "structure, two object detection models have been trained to recognize individual columns and tokens, respectively. A small training set (400 images with approxi- mately 100 annotations each) is curated via the active learning based annotation tool [32] in LayoutParser. The models learn to identify both the categories and regions for each token or column via their distinct visual features. The layout data structure enables easy grouping of the tokens within each column, and rearranging columns to achieve the correct reading orders based on the horizontal position. Errors are identified and rectified via checking the consistency of the model predictions. Therefore, though trained on a small dataset, the pipeline achieves a high level of layout detection accuracy: it achieves a 96.97 AP [19] score across 5 categories for the column detection model, and a 89.23 AP across 4 categories for the token detection model." + "text": "To decipher the complicated layout" }, { "type": "NarrativeText", @@ -2273,32 +2273,32 @@ }, { "type": "UncategorizedText", - "element_id": "0b7709205c824159e1f921b3e01431b6", + "element_id": "869d8bf2a40ba100a2d83b864d9a654f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 16 }, - "text": "largest dataset ever for doc- In: 2019 International Conference on Document IEEE (Sep 2019)." + "text": "ument Analysis and Recognition (ICDAR). pp. 1015–1022. https://doi.org/10.1109/ICDAR.2019.00166" }, { "type": "UncategorizedText", - "element_id": "869d8bf2a40ba100a2d83b864d9a654f", + "element_id": "5ad8687ffef71730e40fbc829ea0d8b6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 16 }, - "text": "ument Analysis and Recognition (ICDAR). pp. 1015–1022. https://doi.org/10.1109/ICDAR.2019.00166" + "text": "layout analysis." }, { "type": "UncategorizedText", - "element_id": "5ad8687ffef71730e40fbc829ea0d8b6", + "element_id": "0b7709205c824159e1f921b3e01431b6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 16 }, - "text": "layout analysis." + "text": "largest dataset ever for doc- In: 2019 International Conference on Document IEEE (Sep 2019)." } ] \ No newline at end of file diff --git a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/65/11/main.PMC6312790.pdf.json b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/65/11/main.PMC6312790.pdf.json index aa199073ee..a6a8775b75 100644 --- a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/65/11/main.PMC6312790.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/65/11/main.PMC6312790.pdf.json @@ -100,34 +100,34 @@ "text": "a b s t r a c t" }, { - "type": "NarrativeText", - "element_id": "5ff19b29d56eb015cac7f80f93c4ae6b", + "type": "UncategorizedText", + "element_id": "c382dd715a85d683f056834c4af7be85", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "This data article contains data related to the research article entitled “enhanced corrosion resistance of stainless steel Type 316 in sulphuric acid solution using eco-friendly waste product” (Sanni et al., 2018). In this data article, a comprehensive effect of waste product and optimized process parameter of the inhibitor in 0.5 M H2SO4 solution was presented using weight loss and potentiody- the inhibitor namic polarization techniques. The presence of (egg shell powder) influenced corrosion resistance of stainless steel. Inhibition efficiency value of 94.74% was recorded as a result of inhibition of the steel by the ionized molecules of the inhibiting compound of the egg shell powder influencing the redox mechan- ism reactions responsible for corrosion and surface deterioration." + "text": "Article history: Received 31 August 2018 Received in revised form 17 November 2018 Accepted 27 November 2018 Available online 30 November 2018" }, { - "type": "UncategorizedText", - "element_id": "c382dd715a85d683f056834c4af7be85", + "type": "Title", + "element_id": "abe4641521caf8385f30e81099f3a8c6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Article history: Received 31 August 2018 Received in revised form 17 November 2018 Accepted 27 November 2018 Available online 30 November 2018" + "text": "Keywords: Corrosion Stainless steel Inhibitor Sulphuric acid" }, { - "type": "Title", - "element_id": "abe4641521caf8385f30e81099f3a8c6", + "type": "NarrativeText", + "element_id": "5ff19b29d56eb015cac7f80f93c4ae6b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Keywords: Corrosion Stainless steel Inhibitor Sulphuric acid" + "text": "This data article contains data related to the research article entitled “enhanced corrosion resistance of stainless steel Type 316 in sulphuric acid solution using eco-friendly waste product” (Sanni et al., 2018). In this data article, a comprehensive effect of waste product and optimized process parameter of the inhibitor in 0.5 M H2SO4 solution was presented using weight loss and potentiody- the inhibitor namic polarization techniques. The presence of (egg shell powder) influenced corrosion resistance of stainless steel. Inhibition efficiency value of 94.74% was recorded as a result of inhibition of the steel by the ionized molecules of the inhibiting compound of the egg shell powder influencing the redox mechan- ism reactions responsible for corrosion and surface deterioration." }, { "type": "NarrativeText", @@ -209,16 +209,6 @@ }, "text": "https://doi.org/10.1016/j.dib.2018.11.134 2352-3409/& 2018 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)." }, - { - "type": "NarrativeText", - "element_id": "9ca201e648ed74cfc838b6661f59addf", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 2 - }, - "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" - }, { "type": "UncategorizedText", "element_id": "549a2fac47d713cc00f2db498ad6b557", @@ -231,23 +221,23 @@ }, { "type": "NarrativeText", - "element_id": "6928b78d26af54b6acb804ed319b5c05", + "element_id": "9ca201e648ed74cfc838b6661f59addf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "How data were acquired" + "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" }, { "type": "NarrativeText", - "element_id": "7ce6ee1aa50d28b85acf544f1db3e25c", + "element_id": "6928b78d26af54b6acb804ed319b5c05", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "The cleaned and weighed specimen was suspended in beakers con- taining 0.5 M H2SO4 solution of different concentrations of egg shell powder. The pre-weighed stainless steel samples were retrieved from the test solutions after every 24 h, cleaned appropriately, dried and reweighed. Raw, analyzed The difference between the weight at a given time and the initial weight of the specimen was taken as the weight loss, which was used to calculate the corrosion rate and inhibition efficiency. Inhibitor concentration, exposure time Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, Pretoria, South Africa Data are available within this article O. Sanni, A. P. I. Popoola, and O. S. I. Fayomi, Enhanced corrosion resistance of stainless steel type 316 in sulphuric acid solution using eco-friendly waste product, Results in Physics, 9 (2018) 225–230." + "text": "How data were acquired" }, { "type": "Title", @@ -279,6 +269,16 @@ }, "text": "Accessibility Related research article" }, + { + "type": "NarrativeText", + "element_id": "7ce6ee1aa50d28b85acf544f1db3e25c", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 2 + }, + "text": "The cleaned and weighed specimen was suspended in beakers con- taining 0.5 M H2SO4 solution of different concentrations of egg shell powder. The pre-weighed stainless steel samples were retrieved from the test solutions after every 24 h, cleaned appropriately, dried and reweighed. Raw, analyzed The difference between the weight at a given time and the initial weight of the specimen was taken as the weight loss, which was used to calculate the corrosion rate and inhibition efficiency. Inhibitor concentration, exposure time Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, Pretoria, South Africa Data are available within this article O. Sanni, A. P. I. Popoola, and O. S. I. Fayomi, Enhanced corrosion resistance of stainless steel type 316 in sulphuric acid solution using eco-friendly waste product, Results in Physics, 9 (2018) 225–230." + }, { "type": "Title", "element_id": "596eda178f8c5adefbae7cfe1bec78c3", @@ -350,94 +350,94 @@ "text": "The results of the experiment are presented in this session. The results obtained from weight loss method for stainless steel Type 316 immersed in 0.5 M H2SO4 solution in the absence and presence of different concentrations of egg shell powder (ES) are presented in Figs. 1–3 respectively. It can be seen clearly from these Figures that the efficiency of egg shell powder increase with the inhibitor con- centration, The increase in its efficiency could be as a result of increase in the constituent molecule" }, { - "type": "UncategorizedText", - "element_id": "624b60c58c9d8bfb6ff1886c2fd605d2", + "type": "Title", + "element_id": "e28e0dc941accc8694040c63091b580c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "30" + "text": ") g m" }, { - "type": "Title", - "element_id": "d300d49efc4cd0982dd6bc3377759ae8", + "type": "UncategorizedText", + "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "10g 8g 6g 4g 2g Control" + "text": "(" }, { "type": "Title", - "element_id": "e28e0dc941accc8694040c63091b580c", + "element_id": "b780e72bd4f737713ae202feb46b5d55", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": ") g m" + "text": "s s o" }, { - "type": "UncategorizedText", - "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", + "type": "Title", + "element_id": "acac86c0e609ca906f632b0e2dacccb2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(" + "text": "l" }, { "type": "Title", - "element_id": "b780e72bd4f737713ae202feb46b5d55", + "element_id": "1bd621f0b71079e0948b0aad011a7f4b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "s s o" + "text": "t h g e W" }, { - "type": "UncategorizedText", - "element_id": "f5ca38f748a1d6eaf726b8a42fb575c3", + "type": "Title", + "element_id": "de7d1b721a1e0632b7cf04edf5032c8e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "20" + "text": "i" }, { - "type": "Title", - "element_id": "acac86c0e609ca906f632b0e2dacccb2", + "type": "UncategorizedText", + "element_id": "624b60c58c9d8bfb6ff1886c2fd605d2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "l" + "text": "30" }, { - "type": "Title", - "element_id": "1bd621f0b71079e0948b0aad011a7f4b", + "type": "UncategorizedText", + "element_id": "f5ca38f748a1d6eaf726b8a42fb575c3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "t h g e W" + "text": "20" }, { "type": "Title", - "element_id": "de7d1b721a1e0632b7cf04edf5032c8e", + "element_id": "d300d49efc4cd0982dd6bc3377759ae8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i" + "text": "10g 8g 6g 4g 2g Control" }, { "type": "UncategorizedText", @@ -559,16 +559,6 @@ }, "text": ") r a e y / m m" }, - { - "type": "UncategorizedText", - "element_id": "a97b042d7bd59d92a46e8ab17f7dff73", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 3 - }, - "text": "1.8" - }, { "type": "NarrativeText", "element_id": "49e7364ce1027887460959b2a757b184", @@ -581,23 +571,23 @@ }, { "type": "Title", - "element_id": "d300d49efc4cd0982dd6bc3377759ae8", + "element_id": "de7d1b721a1e0632b7cf04edf5032c8e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "10g 8g 6g 4g 2g Control" + "text": "i" }, { - "type": "Title", - "element_id": "de7d1b721a1e0632b7cf04edf5032c8e", + "type": "UncategorizedText", + "element_id": "a97b042d7bd59d92a46e8ab17f7dff73", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i" + "text": "1.8" }, { "type": "UncategorizedText", @@ -609,6 +599,16 @@ }, "text": "0.9" }, + { + "type": "Title", + "element_id": "d300d49efc4cd0982dd6bc3377759ae8", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 3 + }, + "text": "10g 8g 6g 4g 2g Control" + }, { "type": "UncategorizedText", "element_id": "c2356069e9d1e79ca924378153cfbbfb", @@ -731,113 +731,113 @@ }, { "type": "UncategorizedText", - "element_id": "85b99d4e3d8e29e46e512f9cca7ba627", + "element_id": "ba5ec51d07a4ac0e951608704431d59a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "2g 4g 6g 8g 10g" + "text": ")" }, { "type": "UncategorizedText", - "element_id": "48449a14a4ff7d79bb7a1b6f3d488eba", + "element_id": "bbf3f11cb5b43e700273a78d12de55e4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "80" + "text": "%" }, { "type": "UncategorizedText", - "element_id": "ba5ec51d07a4ac0e951608704431d59a", + "element_id": "32ebb1abcc1c601ceb9c4e3c4faba0ca", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": ")" + "text": "(" }, { - "type": "UncategorizedText", - "element_id": "bbf3f11cb5b43e700273a78d12de55e4", + "type": "NarrativeText", + "element_id": "bbe120714b80df07396e808f98b3f354", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "%" + "text": "y c n e c i f f" }, { - "type": "UncategorizedText", - "element_id": "ff5a1ae012afa5d4c889c50ad427aaf5", + "type": "Title", + "element_id": "de7d1b721a1e0632b7cf04edf5032c8e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - 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"text": "30" + "text": "2g 4g 6g 8g 10g" }, { "type": "UncategorizedText", @@ -1020,24 +1020,24 @@ "text": "number of inhibitor adsorbed on the surface of stainless steel at higher concentration, in order for the active sites of the stainless steel to be protected with the inhibitor molecules. Cathodic and anodic polarized potential are measured in the presence and absence of ES. Fig. 4 shows the cathodic and anodic polarization curves for stainless steel in 0.5 M H2SO4 solution at different ES concentrations. The electrochemical variables such as polarization resistance (PR), corrosion potential (Ecorr), cor- rosion current (icorr), anodic Tafel constant (ba), cathodic Tafel constant (bc) and corrosion rate (mm/ year) values are presented in Table 1. From the polarization curves and electrochemical parameter, icorr value decreased with the addition of inhibitor in 0.5 M H2SO4. Conversely, the icorr further decrease with an increase in inhibitor concentration indicating that the inhibition effects increase with an increase in the egg shell concentration. The process of egg shell inhibition could be attributed to the formation of egg shell powder adsorbed on stainless steel surface protecting corrosion of stainless steel in H2SO4 medium. The likely mechanism is the egg shell adsorption on stainless steel surface through the heteroatoms electron pair and the conjugated systems in egg shell molecular structure as shown in Fig. 1. When the concentration of inhibitor was increased from 2 to 10 g, the corrosion rate values drastically decreased this result show that waste egg shell powder is an effective corrosion inhibitor for stainless steel in H2SO4 solution. The shift in corrosion potential of stainless steel from Tafel curves and electrochemical data indicate that the inhibitor is a mixed-type corrosion inhibitor." }, { - "type": "NarrativeText", - "element_id": "9ca201e648ed74cfc838b6661f59addf", + "type": "UncategorizedText", + "element_id": "48f89b630677c2cbb70e2ba05bf7a363", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" + "text": "454" }, { - "type": "UncategorizedText", - "element_id": "48f89b630677c2cbb70e2ba05bf7a363", + "type": "NarrativeText", + "element_id": "9ca201e648ed74cfc838b6661f59addf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "454" + "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" }, { "type": "UncategorizedText", @@ -1061,113 +1061,113 @@ }, { "type": "Title", - "element_id": "6978574f5e6e70a2883ea5ea51aa34f7", + "element_id": "362d4a20958df0c88550b9e5d1f2ef5b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "icorr (A/cm2)" + "text": "Inhibitor concentration (g)" }, { "type": "Title", - "element_id": "7507a06cf675785949d6312f1776e444", + "element_id": "bcf00b4904f5661d6baef52e7e09e9b1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Polarization resistance (Ω)" + "text": "bc (V/dec)" }, { "type": "Title", - "element_id": "6d9d421c5383a3abfc3ff6f15c0b16cc", + "element_id": "12e486f4a9b3a1805bf7e95b5d01847b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Corrosion rate (mm/year)" + "text": "ba (V/dec)" }, { "type": "Title", - "element_id": "362d4a20958df0c88550b9e5d1f2ef5b", + "element_id": "7bc31ed7ab5a625735657499f636c1f2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Inhibitor concentration (g)" + "text": "Ecorr (V)" }, { "type": "Title", - "element_id": "bcf00b4904f5661d6baef52e7e09e9b1", + "element_id": "6978574f5e6e70a2883ea5ea51aa34f7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "bc (V/dec)" + "text": "icorr (A/cm2)" }, { "type": "Title", - "element_id": "12e486f4a9b3a1805bf7e95b5d01847b", + "element_id": "7507a06cf675785949d6312f1776e444", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "ba (V/dec)" + "text": "Polarization resistance (Ω)" }, { "type": "Title", - "element_id": "7bc31ed7ab5a625735657499f636c1f2", + "element_id": "6d9d421c5383a3abfc3ff6f15c0b16cc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Ecorr (V)" + "text": "Corrosion rate (mm/year)" }, { "type": "UncategorizedText", - "element_id": "2a789110c863b30156d63234c8a51477", + "element_id": "9492908fadeab22ca81f18f2ba4f4f35", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "(cid:3) 0.9393 (cid:3) 0.8276 (cid:3) 0.8825 (cid:3) 0.8027 (cid:3) 0.5896 (cid:3) 0.5356" + "text": "0 2 4 6 8 10" }, { "type": "UncategorizedText", - "element_id": "9492908fadeab22ca81f18f2ba4f4f35", + "element_id": "12751f842ba5664e7ad255016dbe371b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0 2 4 6 8 10" + "text": "0.0335 1.9460 0.0163 0.3233 0.1240 0.0382" }, { "type": "UncategorizedText", - "element_id": "12751f842ba5664e7ad255016dbe371b", + "element_id": "727d4758bcfadaaf5156b8682cd39810", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0.0335 1.9460 0.0163 0.3233 0.1240 0.0382" + "text": "0.0409 0.0596 0.2369 0.0540 0.0556 0.0086" }, { "type": "UncategorizedText", - "element_id": "727d4758bcfadaaf5156b8682cd39810", + "element_id": "2a789110c863b30156d63234c8a51477", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "0.0409 0.0596 0.2369 0.0540 0.0556 0.0086" + "text": "(cid:3) 0.9393 (cid:3) 0.8276 (cid:3) 0.8825 (cid:3) 0.8027 (cid:3) 0.5896 (cid:3) 0.5356" }, { "type": "UncategorizedText", @@ -1211,23 +1211,23 @@ }, { "type": "UncategorizedText", - "element_id": "1797d9b8b07f302836186c20a19ebd0b", + "element_id": "6b51d431df5d7f141cbececcf79edf3d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "C/0" + "text": "12" }, { "type": "UncategorizedText", - "element_id": "6b51d431df5d7f141cbececcf79edf3d", + "element_id": "1797d9b8b07f302836186c20a19ebd0b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "12" + "text": "C/0" }, { "type": "UncategorizedText", @@ -1410,24 +1410,24 @@ "text": "Fig. 8. SEM/EDX image of stainless steel immersed in 0.5 M H2SO4 solution with the presence of inhibitor." }, { - "type": "NarrativeText", - "element_id": "9ca201e648ed74cfc838b6661f59addf", + "type": "UncategorizedText", + "element_id": "b3a8e0e1f9ab1bfe3a36f231f676f78b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" + "text": "456" }, { - "type": "UncategorizedText", - "element_id": "b3a8e0e1f9ab1bfe3a36f231f676f78b", + "type": "NarrativeText", + "element_id": "9ca201e648ed74cfc838b6661f59addf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "456" + "text": "O. Sanni, A.P.I. Popoola / Data in Brief 22 (2019) 451–457" }, { "type": "Title", @@ -1500,44 +1500,44 @@ "text": "The corrosion rate (CR) was calculated using Eq. (1) [1–5]" }, { - "type": "UncategorizedText", - "element_id": "825c6ae49ec498c873be5355109ca093", + "type": "Title", + "element_id": "cecb8b44c9af4b76e85155170c509729", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "(cid:1) Þ ¼ 87:6W DAT" + "text": "Corrosion rate CRð" }, { "type": "UncategorizedText", - "element_id": "33a2b57b388470db1cb13defbe73dc18", + "element_id": "825c6ae49ec498c873be5355109ca093", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "(cid:3)" + "text": "(cid:1) Þ ¼ 87:6W DAT" }, { - "type": "Title", - "element_id": "53b531237b040202ad24f2c6e37aa792", + "type": "UncategorizedText", + "element_id": "33a2b57b388470db1cb13defbe73dc18", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "ð1Þ" + "text": "(cid:3)" }, { "type": "Title", - "element_id": "cecb8b44c9af4b76e85155170c509729", + "element_id": "53b531237b040202ad24f2c6e37aa792", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "Corrosion rate CRð" + "text": "ð1Þ" }, { "type": "NarrativeText", @@ -1561,23 +1561,23 @@ }, { "type": "Title", - "element_id": "41ceb2965d928f62e5bf4f63da952b22", + "element_id": "5a6824cbd64b72c37057f7d1dbee2798", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "ð2Þ" + "text": "CRo" }, { "type": "Title", - "element_id": "5a6824cbd64b72c37057f7d1dbee2798", + "element_id": "41ceb2965d928f62e5bf4f63da952b22", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "CRo" + "text": "ð2Þ" }, { "type": "Title", @@ -1590,44 +1590,44 @@ "text": "IE ð%Þ ¼ CRo (cid:3) CR" }, { - "type": "UncategorizedText", - "element_id": "3a81feba075b8ca26d6f86f392ff06df", + "type": "Title", + "element_id": "5a6824cbd64b72c37057f7d1dbee2798", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "100 1" + "text": "CRo" }, { "type": "Title", - "element_id": "8e8a7a21640179b38d95ff4450b84e59", + "element_id": "2d711642b726b04401627ca9fbac32f5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "ð3Þ" + "text": "x" }, { - "type": "Title", - "element_id": "2d711642b726b04401627ca9fbac32f5", + "type": "UncategorizedText", + "element_id": "3a81feba075b8ca26d6f86f392ff06df", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "x" + "text": "100 1" }, { "type": "Title", - "element_id": "5a6824cbd64b72c37057f7d1dbee2798", + "element_id": "8e8a7a21640179b38d95ff4450b84e59", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "CRo" + "text": "ð3Þ" }, { "type": "NarrativeText", diff --git a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/75/29/main.PMC6312793.pdf.json b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/75/29/main.PMC6312793.pdf.json index 9125292759..f701f0a641 100644 --- a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/75/29/main.PMC6312793.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-api/75/29/main.PMC6312793.pdf.json @@ -100,24 +100,24 @@ "text": "a b s t r a c t" }, { - "type": "NarrativeText", - "element_id": "8fd297d1a2817570ee2dfbca314e8039", + "type": "UncategorizedText", + "element_id": "ed0a4666ce85e6310a0984f37e0e98f8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "This data article presents a description of a benchmark dataset for the multiple depot vehicle scheduling problem (MDVSP). The MDVSP is to assign vehicles from different depots to timetabled trips to minimize the total cost of empty travel and waiting. The dataset has been developed to evaluate the heuristics of the MDVSP that are presented in “A new formulation and a column generation-based heuristic for the multiple depot vehicle sche- duling problem” (Kulkarni et al., 2018). The dataset contains 60 problem instances of varying size. Researchers can use the dataset to evaluate the future algorithms for the MDVSP and compare the performance with the existing algorithms. The dataset includes a program that can be used to generate new problem instances of the MDVSP." + "text": "Article history: Received 21 November 2018 Received in revised form 13 December 2018 Accepted 15 December 2018 Available online 18 December 2018" }, { - "type": "UncategorizedText", - "element_id": "ed0a4666ce85e6310a0984f37e0e98f8", + "type": "NarrativeText", + "element_id": "8fd297d1a2817570ee2dfbca314e8039", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Article history: Received 21 November 2018 Received in revised form 13 December 2018 Accepted 15 December 2018 Available online 18 December 2018" + "text": "This data article presents a description of a benchmark dataset for the multiple depot vehicle scheduling problem (MDVSP). The MDVSP is to assign vehicles from different depots to timetabled trips to minimize the total cost of empty travel and waiting. The dataset has been developed to evaluate the heuristics of the MDVSP that are presented in “A new formulation and a column generation-based heuristic for the multiple depot vehicle sche- duling problem” (Kulkarni et al., 2018). The dataset contains 60 problem instances of varying size. Researchers can use the dataset to evaluate the future algorithms for the MDVSP and compare the performance with the existing algorithms. The dataset includes a program that can be used to generate new problem instances of the MDVSP." }, { "type": "NarrativeText", @@ -200,34 +200,34 @@ "text": "Subject area Operations research More specific subject area Vehicle scheduling Type of data How data were acquired" }, { - "type": "NarrativeText", - "element_id": "eed804f27c782a8a3643b5d5379099d4", + "type": "Title", + "element_id": "41e0fa358cefcadbb2633ec45ff2d129", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Tables, text files Artificially generated by a C þ þ program on Intels Xeons CPU E5– 2670 v2 with Linux operating system. Raw Sixty randomly generated instances of the MDVSP with the number of depots in (8, 12, 16) and the number of trips in (1500, 2000, 2500, 3000) Randomly generated instances IITB-Monash Research Academy, IIT Bombay, Powai, Mumbai, India. Data can be downloaded from https://orlib.uqcloud.net/ Kulkarni, S., Krishnamoorthy, M., Ranade, A., Ernst, A.T. and Patil, R., 2018. A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem. Transportation Research Part B: Methodological, 118, pp. 457–487 [3]." + "text": "Data format Experimental factors" }, { "type": "Title", - "element_id": "41e0fa358cefcadbb2633ec45ff2d129", + "element_id": "27d70c97431a2bec06d0a89368489dfb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Data format Experimental factors" + "text": "Experimental features Data source location Data accessibility Related research article" }, { - "type": "Title", - "element_id": "27d70c97431a2bec06d0a89368489dfb", + "type": "NarrativeText", + "element_id": "eed804f27c782a8a3643b5d5379099d4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "Experimental features Data source location Data accessibility Related research article" + "text": "Tables, text files Artificially generated by a C þ þ program on Intels Xeons CPU E5– 2670 v2 with Linux operating system. Raw Sixty randomly generated instances of the MDVSP with the number of depots in (8, 12, 16) and the number of trips in (1500, 2000, 2500, 3000) Randomly generated instances IITB-Monash Research Academy, IIT Bombay, Powai, Mumbai, India. Data can be downloaded from https://orlib.uqcloud.net/ Kulkarni, S., Krishnamoorthy, M., Ranade, A., Ernst, A.T. and Patil, R., 2018. A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem. Transportation Research Part B: Methodological, 118, pp. 457–487 [3]." }, { "type": "Title", @@ -249,6 +249,16 @@ }, "text": "(cid:2) The dataset contains 60 different problem instances of the MDVSP that can be used to evaluate the" }, + { + "type": "NarrativeText", + "element_id": "7c8bc2811f71480b433eb6fee2a3bb33", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 2 + }, + "text": "(cid:2) The data provide all the information that is required to model the MDVSP by using the existing" + }, { "type": "Title", "element_id": "bd7d750cb9f652c80c17a264072b8858", @@ -261,13 +271,13 @@ }, { "type": "NarrativeText", - "element_id": "7c8bc2811f71480b433eb6fee2a3bb33", + "element_id": "e69dab6e2bc16d11cfd2d80a804d89fb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(cid:2) The data provide all the information that is required to model the MDVSP by using the existing" + "text": "(cid:2) All the problem instances are available for use without any restrictions. (cid:2) The benchmark solutions and solution time for the problem instances are presented in [3] and can" }, { "type": "Title", @@ -281,13 +291,13 @@ }, { "type": "NarrativeText", - "element_id": "e69dab6e2bc16d11cfd2d80a804d89fb", + "element_id": "1c1d6b35ac0925a35ea3bb4d018e675f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "(cid:2) All the problem instances are available for use without any restrictions. (cid:2) The benchmark solutions and solution time for the problem instances are presented in [3] and can" + "text": "(cid:2) The dataset includes a program that can generate similar problem instances of different sizes." }, { "type": "NarrativeText", @@ -299,16 +309,6 @@ }, "text": "be used for the comparison." }, - { - "type": "NarrativeText", - "element_id": "1c1d6b35ac0925a35ea3bb4d018e675f", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 2 - }, - "text": "(cid:2) The dataset includes a program that can generate similar problem instances of different sizes." - }, { "type": "Title", "element_id": "c2b2b778d53cc9a1cb4dc340476bc5aa", @@ -331,23 +331,23 @@ }, { "type": "UncategorizedText", - "element_id": "e0feab8a8888b2955af1cc1a2acff883", + "element_id": "aea66a7c89c6de4d3e3ed6c1ada31104", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "‘ðm; nÞ’," + "text": "the size," }, { "type": "UncategorizedText", - "element_id": "aea66a7c89c6de4d3e3ed6c1ada31104", + "element_id": "e0feab8a8888b2955af1cc1a2acff883", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "the size," + "text": "‘ðm; nÞ’," }, { "type": "UncategorizedText", @@ -391,33 +391,33 @@ }, { "type": "Title", - "element_id": "7798ae4daad9264de38e67c98f2bd624", + "element_id": "5a15b4000add06e52b66591cd8cac950", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i , a start location, ls" + "text": "i , an end time, te" }, { - "type": "UncategorizedText", - "element_id": "801a0d00a5b76dbd0f039368ee45eda3", + "type": "Title", + "element_id": "7798ae4daad9264de38e67c98f2bd624", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i , and an end location, le i ," + "text": "i , a start location, ls" }, { - "type": "Title", - "element_id": "5a15b4000add06e52b66591cd8cac950", + "type": "UncategorizedText", + "element_id": "801a0d00a5b76dbd0f039368ee45eda3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 2 }, - "text": "i , an end time, te" + "text": "i , and an end location, le i ," }, { "type": "Title", @@ -450,24 +450,24 @@ "text": "All times are in minutes and integers. The planning duration is from 5 a.m. to around midnight. Each instance has two classes of trips, short trips and long trips, with 40% short trips and 60% long trips. The duration of a short trip is less than a total of 45 min and the travel time between the start" }, { - "type": "NarrativeText", - "element_id": "0a1b09ff562f4d063703cbf021ee297f", + "type": "UncategorizedText", + "element_id": "86b700fab5db37977a73700b53a0654b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "S. Kulkarni et al. / Data in Brief 22 (2019) 484–487" + "text": "486" }, { - "type": "UncategorizedText", - "element_id": "86b700fab5db37977a73700b53a0654b", + "type": "NarrativeText", + "element_id": "0a1b09ff562f4d063703cbf021ee297f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "486" + "text": "S. Kulkarni et al. / Data in Brief 22 (2019) 484–487" }, { "type": "NarrativeText", @@ -481,63 +481,63 @@ }, { "type": "NarrativeText", - "element_id": "5201e1037409ea15055e320409a9f5eb", + "element_id": "7e6cb88c34318aaf1a8850c7602bbe6f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i þδ" + "text": "j , the vehicle must travel empty from le j (cid:3)te i Þ. A schedule is given by the sequence in which a vehicle can cover the trips. The MDVSP is to determine the minimum number of schedules to cover all trips that minimizes total time in waiting and empty travel. The following requirements must be satisfied:" }, { "type": "NarrativeText", - "element_id": "43dad32a26a446c5a2c74f3f2328b849", + "element_id": "a18dff87ecdbfa5d5d8a1ed56f7ce734", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": ". If le i ls le i j , otherwise, the vehicle may require waiting at le i for the duration of ðts" + "text": "A trip j can be covered after trip i by the same vehicle, if ts j" }, { - "type": "Title", - "element_id": "a10959d132f2b0d3723ae6b8b77f86b7", + "type": "NarrativeText", + "element_id": "3e549e73bba49a63f20841b5821cfda9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "a ls" + "text": "i to ls" }, { - "type": "Title", - "element_id": "3feb623147ddb3265b5968ce2efb8f6b", + "type": "NarrativeText", + "element_id": "43dad32a26a446c5a2c74f3f2328b849", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Z te" + "text": ". If le i ls le i j , otherwise, the vehicle may require waiting at le i for the duration of ðts" }, { - "type": "NarrativeText", - "element_id": "a18dff87ecdbfa5d5d8a1ed56f7ce734", + "type": "Title", + "element_id": "3feb623147ddb3265b5968ce2efb8f6b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "A trip j can be covered after trip i by the same vehicle, if ts j" + "text": "Z te" }, { "type": "NarrativeText", - "element_id": "7e6cb88c34318aaf1a8850c7602bbe6f", + "element_id": "5201e1037409ea15055e320409a9f5eb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "j , the vehicle must travel empty from le j (cid:3)te i Þ. A schedule is given by the sequence in which a vehicle can cover the trips. The MDVSP is to determine the minimum number of schedules to cover all trips that minimizes total time in waiting and empty travel. The following requirements must be satisfied:" + "text": "i þδ" }, { "type": "Title", @@ -550,14 +550,14 @@ "text": "j" }, { - "type": "NarrativeText", - "element_id": "3e549e73bba49a63f20841b5821cfda9", + "type": "Title", + "element_id": "a10959d132f2b0d3723ae6b8b77f86b7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "i to ls" + "text": "a ls" }, { "type": "NarrativeText", @@ -840,64 +840,64 @@ "text": "1 1 n" }, { - "type": "UncategorizedText", - "element_id": "ea661ceae235dff310398cd2e921e9d8", + "type": "Title", + "element_id": "acac86c0e609ca906f632b0e2dacccb2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "3 m 4" + "text": "l" }, { - "type": "NarrativeText", - "element_id": "d2660f6e66916959c5de8a941bfa89c7", + "type": "UncategorizedText", + "element_id": "ea661ceae235dff310398cd2e921e9d8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "The number of depots, the number of trips, and the number of locations. The number of vehicles rd at each depot d. One line for each trip, i ¼ 1; 2; …; n. Each line provides the start location ls time ts i and the end time te i for the corresponding trip. Each element, δij; where i; j A 1; 2; …; l, refers to the travel time between location i and location j." + "text": "3 m 4" }, { "type": "Title", - "element_id": "08238905e7bba7115b7d7d58fef13ec6", + "element_id": "acac86c0e609ca906f632b0e2dacccb2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "i , the start" + "text": "l" }, { - "type": "Title", - "element_id": "8ee69286d5f681913dbfdeb60bedc572", + "type": "NarrativeText", + "element_id": "d2660f6e66916959c5de8a941bfa89c7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "i , the end location le" + "text": "The number of depots, the number of trips, and the number of locations. The number of vehicles rd at each depot d. One line for each trip, i ¼ 1; 2; …; n. Each line provides the start location ls time ts i and the end time te i for the corresponding trip. Each element, δij; where i; j A 1; 2; …; l, refers to the travel time between location i and location j." }, { "type": "Title", - "element_id": "acac86c0e609ca906f632b0e2dacccb2", + "element_id": "8ee69286d5f681913dbfdeb60bedc572", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "l" + "text": "i , the end location le" }, { "type": "Title", - "element_id": "acac86c0e609ca906f632b0e2dacccb2", + "element_id": "08238905e7bba7115b7d7d58fef13ec6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "l" + "text": "i , the start" }, { "type": "Title", @@ -980,24 +980,24 @@ "text": "[1] G. Carpaneto, M. Dell'Amico, M. Fischetti, P. Toth, A branch and bound algorithm for the multiple depot vehicle scheduling" }, { - "type": "UncategorizedText", - "element_id": "bec40b25a277a08de3415e33284fc76d", + "type": "NarrativeText", + "element_id": "19dee0a4e8fd073350e234b4352b8af6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "problem, Networks 19 (5) (1989) 531–548." + "text": "[2] N. Kliewer, T. Mellouli, L. Suhl, A time–space network based exact optimization model for multi-depot bus scheduling, Eur." }, { - "type": "NarrativeText", - "element_id": "19dee0a4e8fd073350e234b4352b8af6", + "type": "UncategorizedText", + "element_id": "bec40b25a277a08de3415e33284fc76d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "[2] N. Kliewer, T. Mellouli, L. Suhl, A time–space network based exact optimization model for multi-depot bus scheduling, Eur." + "text": "problem, Networks 19 (5) (1989) 531–548." }, { "type": "UncategorizedText", diff --git a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json index 4030404071..2f4b6f5b34 100644 --- a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/biomed-path/07/07/sbaa031.073.PMC7234218.pdf.json @@ -51,53 +51,53 @@ }, { "type": "UncategorizedText", - "element_id": "5ce0f6dc16582eaf81312c412e99ebb9", + "element_id": "87729f38cab913c4c23019736f8609f0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Amedeo Minichino*1, Beata Godlewska1, Philip Cowen1, Philip Burnet1, Belinda Lennox1 1University of Oxford" + "text": "S6. SLEEP ENDOPHENOTYPES OF SCHIZOPHRENIA: A HIGH-DENSITY EEG STUDY IN DRUG-NAÏVE, FIRST EPISODE PSYCHOSIS PATIENTS" }, { "type": "UncategorizedText", - "element_id": "87729f38cab913c4c23019736f8609f0", + "element_id": "e97f1cf1c49f397732e68cf1efb2355e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "S6. SLEEP ENDOPHENOTYPES OF SCHIZOPHRENIA: A HIGH-DENSITY EEG STUDY IN DRUG-NAÏVE, FIRST EPISODE PSYCHOSIS PATIENTS" + "text": "Anna Castelnovo1, Cecilia Casetta2, Francesco Donati3, Renata del Giudice3, Caroline Zangani3, Simone Sarasso3, Armando D’Agostino*3 1Faculty of Biomedical Sciences, Università della Svizzera Italiana, Switzerland; 2Institute of Psychiatry, Psychology and Neuroscience, King’s College London, England; 3Università degli Studi di Milano, Italy" }, { "type": "NarrativeText", - "element_id": "9e7cc386b1093b082bccf936861747aa", + "element_id": "1252f8d8921acac5f706e4402e504a75", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Background: Meta-analytic evidence showed increased levels of periph- eral endocannabinoid metabolites in psychotic illness. Alterations in the endocannabinoid system are believed to compromise glutamate and do- pamine transmission, which play a central role in pathophysiological models of psychosis. I will present preliminary data from an ongoing high-field proton magnetic resonance spectroscopy (MRS) study aimed at investigating the association between peripheral levels of endocannabinoid system metabolites and central glutamate metabolism in individuals at their first non-affective psychotic episode (NA-FEP) and healthy controls. Methods: We expect to recruit 17 NA-FEP and 20 healthy controls by January 2020. Currently, we recruited 12 NA-FEP and 18 healthy controls from two different research facilities (Imperial College London and University of Oxford) as part of a cross-sectional study. Participants un- derwent MRS scanning at 7-T with voxels placed in right dorsolateral prefrontal cortex (right-DLPFC), anterior cingulate cortex (ACC), and oc- cipital cortex. Neuro-metabolites will be calculated using the unsuppressed water signal as reference. Endocannabinoid metabolites were quantified from serum samples, collected during the same imaging session. Results: Analyses are ongoing. Based on previous evidence, expected findings are: (i) reduced glutamate levels in the ACC and right-DLPFC of NA-FEP compared to controls; (ii) increased peripheral endocannabinoid metabolites in NA-FEP compared to controls; and (iii) inverse association between peripheral endocannabinoid metabolites and glutamate levels in ACC and right-DLPFC in NA-FEP Discussion: This study will help clarifying the contribution of peripheral endocannabinoid system to central brain mechanisms of key relevance for psychotic illness. It will also add further evidence on the limited literature on high-resolution characterisation of brain metabolites in early psychosis. Strengths of the study include: (i) use of high-field MRS, which allows the estimation of glutamate-related compounds at higher precision than at lower field strength; (ii) reduced heterogeneity of the clinical sample (only male and NA-FEP). Limitations: small sample size and cross-sectional design." + "text": "Background: Slow waves, the hallmark of the deep nonrapid eye move- ment sleep electroencephalogram (EEG), are critical for restorative sleep and brain plasticity. They arise from the synchronous depolarization and hyperpolarization of millions of cortical neurons and their proper gen- eration and propagation relies upon the integrity of widespread cortico- thalamic networks. Slow wave abnormalities have been reported in patient with Schizophrenia, although with partially contradictory results, probably related to antipsychotic and sedative medications. Recently, their presence and delineation, have been convincingly shown in first-episode psychosis patients (FEP). However, clear evidence of this biomarker at the onset of the disease, prior to any psychopharmacological intervention, remains limited. Moreover, no attempt has been made to elucidate the prognostic meaning of this finding. Methods: We collected whole night sleep high–density electroencephalog- raphy recordings (64-channel BrainAmp, Brain Products GmbH, Gilching, Germany) in 20 drug-naive FEP patients and 20 healthy control subjects (HC). Several clinical psychometric scales as well as neurocognitive tests were administered to all subjects in order to better define psychopatholog- ical status and vulnerability. EEG slow wave activity (SWA, spectral power between 1 and 4 Hz) and several slow wave parameters were computed at each electrode location, including density and amplitude, at each electrode location. Along with a group analysis between FEP and HC, a subgroup analysis was also computed between patients who showed a progression of symptoms to full-blown Schizophrenia (SCZ, n = 10) over the next 12-month follow-up and those who did not (OTH, n = 10). Results: Sleep macro-architecture was globally preserved in FEP patients. SWA (1–4 Hz) was lower in FEP compared to HC but this difference didn’t reach statistical significance. Slow wave density was decreased in FEP compared to HC, with a significance that survived multiple comparison correction over a large fronto-central cluster. Mean amplitude was pre- served. At the subgroup analysis, these results were largely driven by the subgroup of patients with a confirmed diagnosis of SCZ at a 12-month fol- low-up. Indeed, no difference could be found between OTH and HC, while a strong significance was still evident between SCZ and HC." }, { "type": "UncategorizedText", - "element_id": "e97f1cf1c49f397732e68cf1efb2355e", + "element_id": "5ce0f6dc16582eaf81312c412e99ebb9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Anna Castelnovo1, Cecilia Casetta2, Francesco Donati3, Renata del Giudice3, Caroline Zangani3, Simone Sarasso3, Armando D’Agostino*3 1Faculty of Biomedical Sciences, Università della Svizzera Italiana, Switzerland; 2Institute of Psychiatry, Psychology and Neuroscience, King’s College London, England; 3Università degli Studi di Milano, Italy" + "text": "Amedeo Minichino*1, Beata Godlewska1, Philip Cowen1, Philip Burnet1, Belinda Lennox1 1University of Oxford" }, { "type": "NarrativeText", - "element_id": "1252f8d8921acac5f706e4402e504a75", + "element_id": "9e7cc386b1093b082bccf936861747aa", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 1 }, - "text": "Background: Slow waves, the hallmark of the deep nonrapid eye move- ment sleep electroencephalogram (EEG), are critical for restorative sleep and brain plasticity. They arise from the synchronous depolarization and hyperpolarization of millions of cortical neurons and their proper gen- eration and propagation relies upon the integrity of widespread cortico- thalamic networks. Slow wave abnormalities have been reported in patient with Schizophrenia, although with partially contradictory results, probably related to antipsychotic and sedative medications. Recently, their presence and delineation, have been convincingly shown in first-episode psychosis patients (FEP). However, clear evidence of this biomarker at the onset of the disease, prior to any psychopharmacological intervention, remains limited. Moreover, no attempt has been made to elucidate the prognostic meaning of this finding. Methods: We collected whole night sleep high–density electroencephalog- raphy recordings (64-channel BrainAmp, Brain Products GmbH, Gilching, Germany) in 20 drug-naive FEP patients and 20 healthy control subjects (HC). Several clinical psychometric scales as well as neurocognitive tests were administered to all subjects in order to better define psychopatholog- ical status and vulnerability. EEG slow wave activity (SWA, spectral power between 1 and 4 Hz) and several slow wave parameters were computed at each electrode location, including density and amplitude, at each electrode location. Along with a group analysis between FEP and HC, a subgroup analysis was also computed between patients who showed a progression of symptoms to full-blown Schizophrenia (SCZ, n = 10) over the next 12-month follow-up and those who did not (OTH, n = 10). Results: Sleep macro-architecture was globally preserved in FEP patients. SWA (1–4 Hz) was lower in FEP compared to HC but this difference didn’t reach statistical significance. Slow wave density was decreased in FEP compared to HC, with a significance that survived multiple comparison correction over a large fronto-central cluster. Mean amplitude was pre- served. At the subgroup analysis, these results were largely driven by the subgroup of patients with a confirmed diagnosis of SCZ at a 12-month fol- low-up. Indeed, no difference could be found between OTH and HC, while a strong significance was still evident between SCZ and HC." + "text": "Background: Meta-analytic evidence showed increased levels of periph- eral endocannabinoid metabolites in psychotic illness. Alterations in the endocannabinoid system are believed to compromise glutamate and do- pamine transmission, which play a central role in pathophysiological models of psychosis. I will present preliminary data from an ongoing high-field proton magnetic resonance spectroscopy (MRS) study aimed at investigating the association between peripheral levels of endocannabinoid system metabolites and central glutamate metabolism in individuals at their first non-affective psychotic episode (NA-FEP) and healthy controls. Methods: We expect to recruit 17 NA-FEP and 20 healthy controls by January 2020. Currently, we recruited 12 NA-FEP and 18 healthy controls from two different research facilities (Imperial College London and University of Oxford) as part of a cross-sectional study. Participants un- derwent MRS scanning at 7-T with voxels placed in right dorsolateral prefrontal cortex (right-DLPFC), anterior cingulate cortex (ACC), and oc- cipital cortex. Neuro-metabolites will be calculated using the unsuppressed water signal as reference. Endocannabinoid metabolites were quantified from serum samples, collected during the same imaging session. Results: Analyses are ongoing. Based on previous evidence, expected findings are: (i) reduced glutamate levels in the ACC and right-DLPFC of NA-FEP compared to controls; (ii) increased peripheral endocannabinoid metabolites in NA-FEP compared to controls; and (iii) inverse association between peripheral endocannabinoid metabolites and glutamate levels in ACC and right-DLPFC in NA-FEP Discussion: This study will help clarifying the contribution of peripheral endocannabinoid system to central brain mechanisms of key relevance for psychotic illness. It will also add further evidence on the limited literature on high-resolution characterisation of brain metabolites in early psychosis. Strengths of the study include: (i) use of high-field MRS, which allows the estimation of glutamate-related compounds at higher precision than at lower field strength; (ii) reduced heterogeneity of the clinical sample (only male and NA-FEP). Limitations: small sample size and cross-sectional design." }, { "type": "UncategorizedText", diff --git a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json index 80dc48f117..56145d27c7 100644 --- a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json @@ -150,54 +150,54 @@ "text": "Figure 1. Twin Peaks? Headline and Core Inflation (Percent, year over year)" }, { - "type": "Title", - "element_id": "323d79e74460eda1fb0f8d55a2e0ff42", + "type": "UncategorizedText", + "element_id": "808caaef5b114d874a25b7fec21b5516", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Median country Brazil" + "text": "18 16 14 12 10 8 6 4 2 0 –2" }, { - "type": "Title", - "element_id": "49dca65f362fee401292ed7ada96f962", + "type": "UncategorizedText", + "element_id": "28a5aa3897d66de6c31caba99a4c337e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "United States" + "text": "–2" }, { - "type": "Title", - "element_id": "007b2203e9e86a49c3108e9ffd16fbbc", + "type": "NarrativeText", + "element_id": "e26dceaba57a5f670d91ac170e8706d1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Euro area" + "text": "Sources: Haver Analytics; and IMF staff calculations. Note: The figure shows the developments in headline and core inflation across 18 advanced economies and 17 emerging market and developing economies. Core inflation is the change in prices for goods and services, but excluding those for food and energy (or the closest available measure). For the euro area (and other European countries for which the data are available), energy, food, alcohol, and tobacco are excluded. The gray bands depict the 10th to 90th percentiles of inflation across economies." }, { "type": "UncategorizedText", - "element_id": "808caaef5b114d874a25b7fec21b5516", + "element_id": "c2c7be4534a60790d1d18451c91dc138", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "18 16 14 12 10 8 6 4 2 0 –2" + "text": "16 14 12 10 8 6 4 2 0" }, { - "type": "Title", - "element_id": "63e35649dd179389ecc7251e1503489a", + "type": "UncategorizedText", + "element_id": "c7c72889cb49cf43d9bd1f892db1be2c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "1. Headline Inflation" + "text": "Jan. 2019" }, { "type": "UncategorizedText", @@ -211,183 +211,183 @@ }, { "type": "Title", - "element_id": "646612b0a62b59fd13be769b4590a9ac", + "element_id": "63e35649dd179389ecc7251e1503489a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 19" + "text": "1. Headline Inflation" }, { "type": "Title", - "element_id": "7a4f82ed474f82c26a8b867becaf89ba", + "element_id": "b790ab5fcad28bbedb50b568b3adeca2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 20" + "text": "2. Core Inflation" }, { "type": "Title", - "element_id": "6d2f5e3c057e12c92023d5501c3fd075", + "element_id": "323d79e74460eda1fb0f8d55a2e0ff42", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 20" + "text": "Median country Brazil" }, { "type": "Title", - "element_id": "f4a93992a1b09b3fa6200542fd6fde5a", + "element_id": "646612b0a62b59fd13be769b4590a9ac", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 21" + "text": "Jul. 19" }, { "type": "Title", - "element_id": "81db94f58819ee2fd6c05ddef2082ccc", + "element_id": "646612b0a62b59fd13be769b4590a9ac", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 21" + "text": "Jul. 19" }, { "type": "Title", - "element_id": "babfe67b3ecc6b32db9adb9da08274bf", + "element_id": "7a4f82ed474f82c26a8b867becaf89ba", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 22" + "text": "Jan. 20" }, { "type": "Title", - "element_id": "82debf5a182b9b394ad3a9d584a870ef", + "element_id": "7a4f82ed474f82c26a8b867becaf89ba", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 22" + "text": "Jan. 20" }, { "type": "Title", - "element_id": "cc874418b59b7ecb37a2c938783fb5ce", + "element_id": "6d2f5e3c057e12c92023d5501c3fd075", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Nov. 22" + "text": "Jul. 20" }, { - "type": "UncategorizedText", - "element_id": "c2c7be4534a60790d1d18451c91dc138", + "type": "Title", + "element_id": "6d2f5e3c057e12c92023d5501c3fd075", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "16 14 12 10 8 6 4 2 0" + "text": "Jul. 20" }, { "type": "Title", - "element_id": "b790ab5fcad28bbedb50b568b3adeca2", + "element_id": "49dca65f362fee401292ed7ada96f962", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "2. Core Inflation" + "text": "United States" }, { - "type": "UncategorizedText", - "element_id": "28a5aa3897d66de6c31caba99a4c337e", + "type": "Title", + "element_id": "f4a93992a1b09b3fa6200542fd6fde5a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "–2" + "text": "Jan. 21" }, { - "type": "UncategorizedText", - "element_id": "c7c72889cb49cf43d9bd1f892db1be2c", + "type": "Title", + "element_id": "f4a93992a1b09b3fa6200542fd6fde5a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 2019" + "text": "Jan. 21" }, { "type": "Title", - "element_id": "646612b0a62b59fd13be769b4590a9ac", + "element_id": "81db94f58819ee2fd6c05ddef2082ccc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 19" + "text": "Jul. 21" }, { "type": "Title", - "element_id": "7a4f82ed474f82c26a8b867becaf89ba", + "element_id": "81db94f58819ee2fd6c05ddef2082ccc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 20" + "text": "Jul. 21" }, { "type": "Title", - "element_id": "6d2f5e3c057e12c92023d5501c3fd075", + "element_id": "babfe67b3ecc6b32db9adb9da08274bf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 20" + "text": "Jan. 22" }, { "type": "Title", - "element_id": "f4a93992a1b09b3fa6200542fd6fde5a", + "element_id": "babfe67b3ecc6b32db9adb9da08274bf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 21" + "text": "Jan. 22" }, { "type": "Title", - "element_id": "81db94f58819ee2fd6c05ddef2082ccc", + "element_id": "007b2203e9e86a49c3108e9ffd16fbbc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 21" + "text": "Euro area" }, { "type": "Title", - "element_id": "babfe67b3ecc6b32db9adb9da08274bf", + "element_id": "82debf5a182b9b394ad3a9d584a870ef", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 22" + "text": "Jul. 22" }, { "type": "Title", @@ -410,14 +410,14 @@ "text": "Nov. 22" }, { - "type": "NarrativeText", - "element_id": "e26dceaba57a5f670d91ac170e8706d1", + "type": "Title", + "element_id": "cc874418b59b7ecb37a2c938783fb5ce", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Sources: Haver Analytics; and IMF staff calculations. Note: The figure shows the developments in headline and core inflation across 18 advanced economies and 17 emerging market and developing economies. Core inflation is the change in prices for goods and services, but excluding those for food and energy (or the closest available measure). For the euro area (and other European countries for which the data are available), energy, food, alcohol, and tobacco are excluded. The gray bands depict the 10th to 90th percentiles of inflation across economies." + "text": "Nov. 22" }, { "type": "NarrativeText", @@ -720,14 +720,14 @@ "text": "Q4 over Q4 2/" }, { - "type": "Title", - "element_id": "1968c7f7ac8a3b0483f733357bb50b16", + "type": "UncategorizedText", + "element_id": "1bea20e1df19b12013976de2b5e0e3d1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "WEO Projections 1/" + "text": "2021" }, { "type": "Title", @@ -750,34 +750,34 @@ "text": "Projections 2023" }, { - "type": "Title", - "element_id": "b88d850d87e55cb1fd14ae67e5644d57", + "type": "UncategorizedText", + "element_id": "6557739a67283a8de383fc5c0997fbec", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Estimate 2022" + "text": "2024" }, { "type": "Title", - "element_id": "18665f77847d326417463628d8860261", + "element_id": "1968c7f7ac8a3b0483f733357bb50b16", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Projections 2023" + "text": "WEO Projections 1/" }, { "type": "UncategorizedText", - "element_id": "1bea20e1df19b12013976de2b5e0e3d1", + "element_id": "d398b29d3dbbb9bf201d4c7e1c19ff9d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2021" + "text": "2023" }, { "type": "UncategorizedText", @@ -790,24 +790,24 @@ "text": "2024" }, { - "type": "UncategorizedText", - "element_id": "d398b29d3dbbb9bf201d4c7e1c19ff9d", + "type": "Title", + "element_id": "b88d850d87e55cb1fd14ae67e5644d57", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2023" + "text": "Estimate 2022" }, { - "type": "UncategorizedText", - "element_id": "6557739a67283a8de383fc5c0997fbec", + "type": "Title", + "element_id": "18665f77847d326417463628d8860261", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2024" + "text": "Projections 2023" }, { "type": "UncategorizedText", @@ -929,6 +929,26 @@ }, "text": "Advanced Economies United States Euro Area" }, + { + "type": "Title", + "element_id": "18231df9f753f2eca887585247231761", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 7 + }, + "text": "Germany France Italy Spain" + }, + { + "type": "Title", + "element_id": "7559320d044a32fbb21a7a8da25e9045", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 7 + }, + "text": "Japan United Kingdom Canada Other Advanced Economies 3/" + }, { "type": "UncategorizedText", "element_id": "2a9680555d457b6da4b6748492bb6f3d", @@ -1021,203 +1041,183 @@ }, { "type": "Title", - "element_id": "18231df9f753f2eca887585247231761", + "element_id": "a4ca51cd6c74adf51f6e9ce60165d047", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Germany France Italy Spain" + "text": "Emerging Market and Developing Economies Emerging and Developing Asia" }, { "type": "Title", - "element_id": "7559320d044a32fbb21a7a8da25e9045", + "element_id": "d5d29f012a1237803ee7e623a134117a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Japan United Kingdom Canada Other Advanced Economies 3/" + "text": "China India 4/" }, { "type": "Title", - "element_id": "a4ca51cd6c74adf51f6e9ce60165d047", + "element_id": "8325885b8155742cebc672e0d7072a7d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Emerging Market and Developing Economies Emerging and Developing Asia" + "text": "Emerging and Developing Europe" }, { - "type": "UncategorizedText", - "element_id": "a7143daa9de8af6e0c465ca1354d45b6", + "type": "Title", + "element_id": "33a3d8ed92b0709ba525369922e51387", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "6.7 7.4 8.4 8.7 6.9 4.7 7.0 5.0 4.7 4.5 3.2 4.7 3.6 4.9" + "text": "Russia" }, { - "type": "UncategorizedText", - "element_id": "53bcbc5ff007dd49a07f6fb79ef96ef9", + "type": "Title", + "element_id": "ad1094978303f5aa32665083ee1ed934", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "3.9 4.3 3.0 6.8 0.7 –2.2 3.9 3.1 3.1 5.3 8.7 3.8 3.0 2.6" + "text": "Latin America and the Caribbean" }, { - "type": "UncategorizedText", - "element_id": "1ea8f3c3db2cb6c75f21ebf26acc28a5", + "type": "Title", + "element_id": "24af2841400373443d80b6c91180918b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "4.0 5.3 5.2 6.1 1.5 0.3 1.8 1.2 1.7 3.2 2.6 3.8 3.2 1.2" + "text": "Middle East and Central Asia" }, { - "type": "UncategorizedText", - "element_id": "9d1bc5abd6f3e9c4c6ccb572ae521387", + "type": "Title", + "element_id": "e30a554d7d1cbf308651f8c267ad6872", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "4.2 5.2 4.5 6.8 2.6 2.1 2.1 1.5 1.6 3.7 3.4 4.1 2.9 1.3" + "text": "Brazil Mexico" }, { - "type": "UncategorizedText", - "element_id": "e06f96c6cf56b11e98615192247171fa", + "type": "Title", + "element_id": "b2800ff802361713acee893ebae272f6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "0.3 0.4 0.8 0.0 0.9 2.6 0.1 0.2 0.5 –0.4 –1.1 0.1 0.2 0.1" + "text": "Saudi Arabia Sub-Saharan Africa" }, { - "type": "UncategorizedText", - "element_id": "4d702c47ea48fa0dca98ce691995cc1b", + "type": "Title", + "element_id": "05704f84f4326b5f53a04d62f7ad62fc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "–0.1 0.0 0.0 0.0 0.1 0.6 –0.3 –0.4 –0.2 0.2 0.5 0.0 0.0 0.0" + "text": "Nigeria South Africa" }, { "type": "UncategorizedText", - "element_id": "d7b26ee43ca5481505ca9eb7c3b29b2c", + "element_id": "a7143daa9de8af6e0c465ca1354d45b6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2.5 3.4 2.9 4.3 –2.0 –4.1 2.6 2.8 3.7 . . . 4.6 . . . 2.6 3.0" + "text": "6.7 7.4 8.4 8.7 6.9 4.7 7.0 5.0 4.7 4.5 3.2 4.7 3.6 4.9" }, { "type": "UncategorizedText", - "element_id": "f4e79a2ba19a5b842cff288f8e4eafd0", + "element_id": "53bcbc5ff007dd49a07f6fb79ef96ef9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "5.0 6.2 5.9 7.0 3.5 1.0 1.9 0.8 1.1 . . . 2.7 . . . 3.1 0.5" + "text": "3.9 4.3 3.0 6.8 0.7 –2.2 3.9 3.1 3.1 5.3 8.7 3.8 3.0 2.6" }, { "type": "UncategorizedText", - "element_id": "07adb8acdd66b5d2490e542ae0604b71", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 7 - }, - "text": "4.1 4.9 4.1 7.1 2.8 2.0 1.9 2.2 1.9 . . . 3.5 . . . 2.9 1.8" - }, - { - "type": "Title", - "element_id": "d5d29f012a1237803ee7e623a134117a", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 7 - }, - "text": "China India 4/" - }, - { - "type": "Title", - "element_id": "8325885b8155742cebc672e0d7072a7d", + "element_id": "1ea8f3c3db2cb6c75f21ebf26acc28a5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Emerging and Developing Europe" + "text": "4.0 5.3 5.2 6.1 1.5 0.3 1.8 1.2 1.7 3.2 2.6 3.8 3.2 1.2" }, { - "type": "Title", - "element_id": "33a3d8ed92b0709ba525369922e51387", + "type": "UncategorizedText", + "element_id": "9d1bc5abd6f3e9c4c6ccb572ae521387", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Russia" + "text": "4.2 5.2 4.5 6.8 2.6 2.1 2.1 1.5 1.6 3.7 3.4 4.1 2.9 1.3" }, { - "type": "Title", - "element_id": "ad1094978303f5aa32665083ee1ed934", + "type": "UncategorizedText", + "element_id": "e06f96c6cf56b11e98615192247171fa", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Latin America and the Caribbean" + "text": "0.3 0.4 0.8 0.0 0.9 2.6 0.1 0.2 0.5 –0.4 –1.1 0.1 0.2 0.1" }, { - "type": "Title", - "element_id": "e30a554d7d1cbf308651f8c267ad6872", + "type": "UncategorizedText", + "element_id": "4d702c47ea48fa0dca98ce691995cc1b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Brazil Mexico" + "text": "–0.1 0.0 0.0 0.0 0.1 0.6 –0.3 –0.4 –0.2 0.2 0.5 0.0 0.0 0.0" }, { - "type": "Title", - "element_id": "24af2841400373443d80b6c91180918b", + "type": "UncategorizedText", + "element_id": "d7b26ee43ca5481505ca9eb7c3b29b2c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Middle East and Central Asia" + "text": "2.5 3.4 2.9 4.3 –2.0 –4.1 2.6 2.8 3.7 . . . 4.6 . . . 2.6 3.0" }, { - "type": "Title", - "element_id": "b2800ff802361713acee893ebae272f6", + "type": "UncategorizedText", + "element_id": "f4e79a2ba19a5b842cff288f8e4eafd0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Saudi Arabia Sub-Saharan Africa" + "text": "5.0 6.2 5.9 7.0 3.5 1.0 1.9 0.8 1.1 . . . 2.7 . . . 3.1 0.5" }, { - "type": "Title", - "element_id": "05704f84f4326b5f53a04d62f7ad62fc", + "type": "UncategorizedText", + "element_id": "07adb8acdd66b5d2490e542ae0604b71", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Nigeria South Africa" + "text": "4.1 4.9 4.1 7.1 2.8 2.0 1.9 2.2 1.9 . . . 3.5 . . . 2.9 1.8" }, { "type": "UncategorizedText", @@ -1970,24 +1970,24 @@ "text": "Overall, financial stability risks remain elevated as investors reassess their inflation and monetary policy outlook. Global financial conditions have eased somewhat since the October 2022 Global Financial Stability Report, driven largely by changing market expectations regarding the interest rate cycle (Figure 1.1). While the expected peak in policy rates—the terminal rate—has risen, markets now also expect the subsequent fall in rates will be significantly faster, and further, than what was forecast in October (Figure 1.2). As a result, global bond yields have recently declined, corporate spreads have tightened, and equity markets have rebounded. That said, central banks are likely to continue to tighten monetary policy to fight inflation, and concerns that this restrictive stance could tip the economy into a recession have increased in major advanced economies." }, { - "type": "Title", - "element_id": "57de33ba9eaa9e5980d4cf6da83abf46", + "type": "NarrativeText", + "element_id": "e118be83abfed92b8969eca98bb4d53b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Figure 1.1. Global Financial Conditions: Selected Regions (Standard deviations from mean)" + "text": "Slowing aggregate demand and weaker-than-expected inflation prints in some major advanced economies have prompted investors’ anticipation of a further reduction in the pace of future policy rate hikes. Corporate earnings forecasts have been cut due to headwinds from slowing demand, and margins have contracted across most regions. In addition, survey-based probabilities of recession have been increasing, particularly in the United States and Europe. However, upside risks to the inflation outlook remain. Despite the recent moderation in headline inflation, core inflation remains stubbornly high across most regions, labor markets are still tight, energy prices remain pressured by Russia’s ongoing war in Ukraine, and supply chain disruptions may reappear. To keep these risks in check, financial conditions will likely need to tighten further. If not, central banks may need to increase policy rates even more in order to achieve their inflation objectives." }, { "type": "Title", - "element_id": "4255f2d53f6408c450b02b249d53c220", + "element_id": "57de33ba9eaa9e5980d4cf6da83abf46", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "United States Euro area China Other AEs Other EMs" + "text": "Figure 1.1. Global Financial Conditions: Selected Regions (Standard deviations from mean)" }, { "type": "UncategorizedText", @@ -1999,16 +1999,6 @@ }, "text": "7" }, - { - "type": "Title", - "element_id": "53d79cec96694df67ce3baff95d8a2e3", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 11 - }, - "text": "October 2022 GFSR" - }, { "type": "UncategorizedText", "element_id": "e7f6c011776e8db7cd330b54174fd76f", @@ -2039,6 +2029,26 @@ }, "text": "4" }, + { + "type": "Title", + "element_id": "4255f2d53f6408c450b02b249d53c220", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 11 + }, + "text": "United States Euro area China Other AEs Other EMs" + }, + { + "type": "Title", + "element_id": "53d79cec96694df67ce3baff95d8a2e3", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 11 + }, + "text": "October 2022 GFSR" + }, { "type": "UncategorizedText", "element_id": "4e07408562bedb8b60ce05c1decfe3ad", @@ -2121,73 +2131,73 @@ }, { "type": "UncategorizedText", - "element_id": "785329d8f1c63e8d0cdeedba9e6bc2ea", + "element_id": "aacd834b5cdc64a329e27649143406dd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "10 10" + "text": "06" }, { "type": "UncategorizedText", - "element_id": "1e46bf7c5134da75e3a2aae852d7bddf", + "element_id": "785329d8f1c63e8d0cdeedba9e6bc2ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "12 12" + "text": "10 10" }, { "type": "UncategorizedText", - "element_id": "c81a1234a265c680bbc9e96e73073acd", + "element_id": "1e46bf7c5134da75e3a2aae852d7bddf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "14 16 14" + "text": "12 12" }, { "type": "UncategorizedText", - "element_id": "99cb7a0185216a0acb0ed918e7058868", + "element_id": "c81a1234a265c680bbc9e96e73073acd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "18 18" + "text": "14 16 14" }, { "type": "UncategorizedText", - "element_id": "0c5e98c11d7bb005adbaf731ebfbbb2c", + "element_id": "b17ef6d19c7a5b1ee83b907c595526dc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "20 22 22" + "text": "16" }, { "type": "UncategorizedText", - "element_id": "aacd834b5cdc64a329e27649143406dd", + "element_id": "99cb7a0185216a0acb0ed918e7058868", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "06" + "text": "18 18" }, { "type": "UncategorizedText", - "element_id": "b17ef6d19c7a5b1ee83b907c595526dc", + "element_id": "0c5e98c11d7bb005adbaf731ebfbbb2c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "16" + "text": "20 22 22" }, { "type": "UncategorizedText", @@ -2209,16 +2219,6 @@ }, "text": "Sources: Bloomberg Finance L.P.; Haver Analytics; national data sources; and IMF staff calculations. Note: AEs = advanced economies; EMs = emerging markets. GFSR = Global Financial Stability Report." }, - { - "type": "NarrativeText", - "element_id": "e118be83abfed92b8969eca98bb4d53b", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 11 - }, - "text": "Slowing aggregate demand and weaker-than-expected inflation prints in some major advanced economies have prompted investors’ anticipation of a further reduction in the pace of future policy rate hikes. Corporate earnings forecasts have been cut due to headwinds from slowing demand, and margins have contracted across most regions. In addition, survey-based probabilities of recession have been increasing, particularly in the United States and Europe. However, upside risks to the inflation outlook remain. Despite the recent moderation in headline inflation, core inflation remains stubbornly high across most regions, labor markets are still tight, energy prices remain pressured by Russia’s ongoing war in Ukraine, and supply chain disruptions may reappear. To keep these risks in check, financial conditions will likely need to tighten further. If not, central banks may need to increase policy rates even more in order to achieve their inflation objectives." - }, { "type": "Title", "element_id": "6ef230728534d871e5126e2a55e12b26", @@ -2251,23 +2251,23 @@ }, { "type": "UncategorizedText", - "element_id": "ef2d127de37b942baad06145e54b0c61", + "element_id": "e7f6c011776e8db7cd330b54174fd76f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "5" + "text": "6" }, { - "type": "UncategorizedText", - "element_id": "e7f6c011776e8db7cd330b54174fd76f", + "type": "Title", + "element_id": "7d4f55875c970d850a152ba1d5ba02a5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "6" + "text": "1. United States" }, { "type": "Title", @@ -2280,104 +2280,104 @@ "text": "2. Euro area" }, { - "type": "Title", - "element_id": "7d4f55875c970d850a152ba1d5ba02a5", + "type": "UncategorizedText", + "element_id": "ef2d127de37b942baad06145e54b0c61", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "1. United States" + "text": "5" }, { "type": "UncategorizedText", - "element_id": "ef2d127de37b942baad06145e54b0c61", + "element_id": "4b227777d4dd1fc61c6f884f48641d02", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "5" + "text": "4" }, { "type": "UncategorizedText", - "element_id": "4b227777d4dd1fc61c6f884f48641d02", + "element_id": "4e07408562bedb8b60ce05c1decfe3ad", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "4" + "text": "3" }, { "type": "UncategorizedText", - "element_id": "4b227777d4dd1fc61c6f884f48641d02", + "element_id": "d4735e3a265e16eee03f59718b9b5d03", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "4" + "text": "2" }, { "type": "UncategorizedText", - "element_id": "4e07408562bedb8b60ce05c1decfe3ad", + "element_id": "6b86b273ff34fce19d6b804eff5a3f57", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "3" + "text": "1" }, { - "type": "UncategorizedText", - "element_id": "4e07408562bedb8b60ce05c1decfe3ad", + "type": "Title", + "element_id": "49cf8421218222b21a0fc54ffce584c9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "3" + "text": "Oct. 22" }, { - "type": "UncategorizedText", - "element_id": "d4735e3a265e16eee03f59718b9b5d03", + "type": "Title", + "element_id": "24a234895630131d612fc1b4605a256e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "2" + "text": "Apr. 23" }, { - "type": "UncategorizedText", - "element_id": "d4735e3a265e16eee03f59718b9b5d03", + "type": "Title", + "element_id": "914e31edcbd035dbe9f1cfb7b29089a9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "2" + "text": "Oct. 23" }, { - "type": "UncategorizedText", - "element_id": "6b86b273ff34fce19d6b804eff5a3f57", + "type": "Title", + "element_id": "d8478f45b9790d52201238244d0e9698", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "1" + "text": "Dec. 24" }, { - "type": "UncategorizedText", - "element_id": "6b86b273ff34fce19d6b804eff5a3f57", + "type": "Title", + "element_id": "fe1cc1c654c8a4fde402cfe2426326ef", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "1" + "text": "Dec. 26" }, { "type": "Title", @@ -2430,54 +2430,54 @@ "text": "Dec. 26" }, { - "type": "Title", - "element_id": "49cf8421218222b21a0fc54ffce584c9", + "type": "UncategorizedText", + "element_id": "ef2d127de37b942baad06145e54b0c61", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Oct. 22" + "text": "5" }, { - "type": "Title", - "element_id": "24a234895630131d612fc1b4605a256e", + "type": "UncategorizedText", + "element_id": "4b227777d4dd1fc61c6f884f48641d02", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Apr. 23" + "text": "4" }, { - "type": "Title", - "element_id": "914e31edcbd035dbe9f1cfb7b29089a9", + "type": "UncategorizedText", + "element_id": "4e07408562bedb8b60ce05c1decfe3ad", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Oct. 23" + "text": "3" }, { - "type": "Title", - "element_id": "d8478f45b9790d52201238244d0e9698", + "type": "UncategorizedText", + "element_id": "d4735e3a265e16eee03f59718b9b5d03", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Dec. 24" + "text": "2" }, { - "type": "Title", - "element_id": "fe1cc1c654c8a4fde402cfe2426326ef", + "type": "UncategorizedText", + "element_id": "6b86b273ff34fce19d6b804eff5a3f57", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Dec. 26" + "text": "1" }, { "type": "NarrativeText", diff --git a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/Silent-Giant-(1).pdf.json b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/Silent-Giant-(1).pdf.json index 4474a4ae2f..2f6c16233d 100644 --- a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/Silent-Giant-(1).pdf.json +++ b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/Silent-Giant-(1).pdf.json @@ -179,16 +179,6 @@ }, "text": " Marine" }, - { - "type": "Title", - "element_id": "d04999bf99ea28fc8a6b20318caac58c", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 4 - }, - "text": " CSP" - }, { "type": "UncategorizedText", "element_id": "9925953f1faef050547e5f7b811c3f7d", @@ -201,13 +191,13 @@ }, { "type": "Title", - "element_id": "8af26217282646d0f64d3e3211f47512", + "element_id": "d04999bf99ea28fc8a6b20318caac58c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": " Solar PV" + "text": " CSP" }, { "type": "UncategorizedText", @@ -219,6 +209,16 @@ }, "text": "35,000" }, + { + "type": "Title", + "element_id": "8af26217282646d0f64d3e3211f47512", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 4 + }, + "text": " Solar PV" + }, { "type": "Title", "element_id": "6e28663850f2b50ee6af2d4477b410be", @@ -259,16 +259,6 @@ }, "text": "h W T" }, - { - "type": "Title", - "element_id": "bde9df80639b681edb85ace46b4d4600", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 4 - }, - "text": " Bioenergy" - }, { "type": "UncategorizedText", "element_id": "c7e6673590d2426f635c9be70bd8f057", @@ -281,13 +271,13 @@ }, { "type": "Title", - "element_id": "b449cd843dc44ab907e1e9ed9c30d92e", + "element_id": "bde9df80639b681edb85ace46b4d4600", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": " Hydro" + "text": " Bioenergy" }, { "type": "UncategorizedText", @@ -299,6 +289,16 @@ }, "text": "20,000" }, + { + "type": "Title", + "element_id": "b449cd843dc44ab907e1e9ed9c30d92e", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 4 + }, + "text": " Hydro" + }, { "type": "Title", "element_id": "f35457739b3bd74c61625c986c844726", @@ -350,24 +350,24 @@ "text": " Oil" }, { - "type": "Title", - "element_id": "90ad0c8c14253135efd14645e0156145", + "type": "UncategorizedText", + "element_id": "b2008c37ee3a7cf7ba87f5ad50dd9e11", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": " Coal" + "text": "5,000" }, { - "type": "UncategorizedText", - "element_id": "b2008c37ee3a7cf7ba87f5ad50dd9e11", + "type": "Title", + "element_id": "90ad0c8c14253135efd14645e0156145", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "5,000" + "text": " Coal" }, { "type": "UncategorizedText", @@ -820,54 +820,54 @@ "text": "0" }, { - "type": "Title", - "element_id": "8e2f99a9826b1b316f7690290f32b31f", + "type": "NarrativeText", + "element_id": "4b5ebf5890b9c61b43c5daf4c40cbab0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "O nshore Wind" + "text": "C o m" }, { "type": "Title", - "element_id": "53209d7cc67427ba22ec6d878fc8d421", + "element_id": "8fd5206adbbb7a132889e4161057d4cf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Offshore Wind" + "text": "m ercial Photovoltaic" }, { "type": "Title", - "element_id": "6dc76d1e1c35d4253537250288157d0c", + "element_id": "8e2f99a9826b1b316f7690290f32b31f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - 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"text": "0" + "text": "1.78" }, { "type": "Title", @@ -1170,74 +1180,64 @@ "text": "Offshore wind" }, { - "type": "NarrativeText", - "element_id": "50a78acc78a3c5b4acc8c439af743a0a", + "type": "UncategorizedText", + "element_id": "77e43ef38dbfcec0511535d9c7dbee5c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "O nshore wind (G erm any)" + "text": "(U K)" }, { - "type": "Title", - "element_id": "6c25ebfc9ffd2510c4c41d4bd5cb7ea9", + "type": "NarrativeText", + "element_id": "50a78acc78a3c5b4acc8c439af743a0a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "C oal" + "text": "O nshore wind (G erm any)" }, { - "type": "Title", - "element_id": "2378bdd2cf4f491cf401e6b215cbb4fd", + "type": "UncategorizedText", + "element_id": "f1ced6d8a7d437fd3748f56bb2358f9a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "Oil" + "text": "0.245" }, { "type": "Title", - "element_id": "4fabb98454d019811a732c4a09f31bf0", + "element_id": "bbf2011ddebee240452a3ab98416afb4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "N atural gas" + "text": "S olar P V" }, { - "type": "Title", - "element_id": "f280c2a253ebd5a7389dd0790fcbd56c", + "type": "UncategorizedText", + "element_id": "efc293f64a092b9bfe153be9357f9580", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "N uclear*" + "text": "<0.01" }, { "type": "Title", - "element_id": "bbf2011ddebee240452a3ab98416afb4", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 8 - }, - "text": "S olar P V" - }, - { - "type": "UncategorizedText", - "element_id": "77e43ef38dbfcec0511535d9c7dbee5c", + "element_id": "f280c2a253ebd5a7389dd0790fcbd56c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "(U K)" + "text": "N uclear*" }, { "type": "NarrativeText", @@ -1280,24 +1280,24 @@ "text": "100" }, { - "type": "Title", - "element_id": "90ad0c8c14253135efd14645e0156145", + "type": "UncategorizedText", + "element_id": "69f59c273b6e669ac32a6dd5e1b2cb63", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": " Coal" + "text": "90" }, { - "type": "UncategorizedText", - "element_id": "69f59c273b6e669ac32a6dd5e1b2cb63", + "type": "Title", + "element_id": "90ad0c8c14253135efd14645e0156145", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "90" + "text": " Coal" }, { "type": "Title", @@ -1329,16 +1329,6 @@ }, "text": " Biofuels/Waste" }, - { - "type": "Title", - "element_id": "c4fad0ce9772d241be8c8624896ada86", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 8 - }, - "text": " Wind/Solar" - }, { "type": "UncategorizedText", "element_id": "ff5a1ae012afa5d4c889c50ad427aaf5", @@ -1351,13 +1341,13 @@ }, { "type": "Title", - "element_id": "b449cd843dc44ab907e1e9ed9c30d92e", + "element_id": "c4fad0ce9772d241be8c8624896ada86", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": " Hydro" + "text": " Wind/Solar" }, { "type": "UncategorizedText", @@ -1369,6 +1359,16 @@ }, "text": "60" }, + { + "type": "Title", + "element_id": "b449cd843dc44ab907e1e9ed9c30d92e", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 8 + }, + "text": " Hydro" + }, { "type": "Title", "element_id": "f35457739b3bd74c61625c986c844726", @@ -1381,23 +1381,23 @@ }, { "type": "UncategorizedText", - "element_id": "1a6562590ef19d1045d06c4055742d38", + "element_id": "bbf3f11cb5b43e700273a78d12de55e4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "50" + "text": "%" }, { "type": "UncategorizedText", - "element_id": "bbf3f11cb5b43e700273a78d12de55e4", + "element_id": "1a6562590ef19d1045d06c4055742d38", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "%" + "text": "50" }, { "type": "UncategorizedText", @@ -1510,24 +1510,24 @@ "text": "600" }, { - "type": "Title", - "element_id": "baa49be4a9f9fab3b991718e0adb565e", + "type": "UncategorizedText", + "element_id": "0604cd3138feed202ef293e062da2f47", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Non-hydro" + "text": "500" }, { - "type": "UncategorizedText", - "element_id": "0604cd3138feed202ef293e062da2f47", + "type": "Title", + "element_id": "baa49be4a9f9fab3b991718e0adb565e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "500" + "text": " Non-hydro" }, { "type": "Title", @@ -1541,13 +1541,13 @@ }, { "type": "Title", - "element_id": "f35457739b3bd74c61625c986c844726", + "element_id": "563a2980d46c81119e1d7d952b375a41", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Nuclear" + "text": "h W T" }, { "type": "UncategorizedText", @@ -1560,34 +1560,34 @@ "text": "400" }, { - "type": "Title", - "element_id": "f6e172956a9472fa43f9a895f99c2836", + "type": "UncategorizedText", + "element_id": "983bd614bb5afece5ab3b6023f71147c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Natural gas" + "text": "300" }, { "type": "Title", - "element_id": "563a2980d46c81119e1d7d952b375a41", + "element_id": "f35457739b3bd74c61625c986c844726", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "h W T" + "text": " Nuclear" }, { - "type": "UncategorizedText", - "element_id": "983bd614bb5afece5ab3b6023f71147c", + "type": "Title", + "element_id": "f6e172956a9472fa43f9a895f99c2836", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "300" + "text": " Natural gas" }, { "type": "Title", @@ -1600,24 +1600,24 @@ "text": " Hydro" }, { - "type": "Title", - "element_id": "b001a2374d44e3085e712bb40f66270e", + "type": "UncategorizedText", + "element_id": "27badc983df1780b60c2b3fa9d3a19a0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Oil" + "text": "200" }, { - "type": "UncategorizedText", - "element_id": "27badc983df1780b60c2b3fa9d3a19a0", + "type": "Title", + "element_id": "b001a2374d44e3085e712bb40f66270e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "200" + "text": " Oil" }, { "type": "Title", @@ -1789,16 +1789,6 @@ }, "text": "i" }, - { - "type": "NarrativeText", - "element_id": "de72de35f0092bdd3107011f3be18dc0", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 10 - }, - "text": "International Energy Agency (2018), World Energy Outlook 2018. Data accessed from https://www.iea.org/weo/ – Based on the New Policies Scenario, which incorporates existing energy policies as well as an assessment of the results likely to stem from the implementation of announced policy intentions – with visual modification by World Nuclear Association. International Energy Agency (n.d.), Statistics. Accessed from: https://www.iea.org/statistics/?country=WORLD&year=2016&category=Electricity&indicator=ElecGenByFuel&mode =chart&dataTable=ELECTRICITYANDHEAT – with visual modifications by World Nuclear Association. International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ Intergovernmental Panel on Climate Change (2018), Special Report on Global Warming of 1.5 °C. Accessed from: https://www.ipcc.ch/sr15/ International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ International Energy Agency & OECD Nuclear Energy Agency (2015), Projected Costs of generating Electricity – 2015 Edition. Accessed from: https://www.oecd-nea.org/ndd/pubs/2015/7057-proj-costs-electricity-2015.pdf International Atomic Energy Agency (2015), Technical challenges in the application and licensing of digital instrumentation and control systems in nuclear power plants. Accessed from: https://www-pub.iaea.org/MTCD/ Publications/PDF/P1695_web.pdf" - }, { "type": "Title", "element_id": "5d7f49449ab22deac22d767b89549c55", @@ -1861,23 +1851,23 @@ }, { "type": "NarrativeText", - "element_id": "b6396ecd6f60e3dcca17c045c00846c1", + "element_id": "de72de35f0092bdd3107011f3be18dc0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "viii Paul-Scherrer Institute. Data for nuclear accidents modified to reflect UNSCEAR findings/recommendations (2012)" + "text": "International Energy Agency (2018), World Energy Outlook 2018. Data accessed from https://www.iea.org/weo/ – Based on the New Policies Scenario, which incorporates existing energy policies as well as an assessment of the results likely to stem from the implementation of announced policy intentions – with visual modification by World Nuclear Association. International Energy Agency (n.d.), Statistics. Accessed from: https://www.iea.org/statistics/?country=WORLD&year=2016&category=Electricity&indicator=ElecGenByFuel&mode =chart&dataTable=ELECTRICITYANDHEAT – with visual modifications by World Nuclear Association. International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ Intergovernmental Panel on Climate Change (2018), Special Report on Global Warming of 1.5 °C. Accessed from: https://www.ipcc.ch/sr15/ International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ International Energy Agency & OECD Nuclear Energy Agency (2015), Projected Costs of generating Electricity – 2015 Edition. Accessed from: https://www.oecd-nea.org/ndd/pubs/2015/7057-proj-costs-electricity-2015.pdf International Atomic Energy Agency (2015), Technical challenges in the application and licensing of digital instrumentation and control systems in nuclear power plants. Accessed from: https://www-pub.iaea.org/MTCD/ Publications/PDF/P1695_web.pdf" }, { - "type": "UncategorizedText", - "element_id": "5897aff759a5cc8d94710101c73af296", + "type": "NarrativeText", + "element_id": "b6396ecd6f60e3dcca17c045c00846c1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "and NRC SOARCA study 2015 International Energy Agency (2018), Electricity Information 2018 https://webstore.iea.org/electricity-information-2018-overview Ibid." + "text": "viii Paul-Scherrer Institute. Data for nuclear accidents modified to reflect UNSCEAR findings/recommendations (2012)" }, { "type": "Title", @@ -1899,6 +1889,16 @@ }, "text": "x" }, + { + "type": "UncategorizedText", + "element_id": "5897aff759a5cc8d94710101c73af296", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 10 + }, + "text": "and NRC SOARCA study 2015 International Energy Agency (2018), Electricity Information 2018 https://webstore.iea.org/electricity-information-2018-overview Ibid." + }, { "type": "UncategorizedText", "element_id": "cd7669ea7d8c7961fdbf51c7fec05db7", @@ -1920,24 +1920,24 @@ "text": "8" }, { - "type": "Title", - "element_id": "2ef1a5c0752085d3a6935132ad9e597c", + "type": "UncategorizedText", + "element_id": "481e5a54650b0a4ac7bc2568ddad436d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" + "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" }, { - "type": "UncategorizedText", - "element_id": "481e5a54650b0a4ac7bc2568ddad436d", + "type": "Title", + "element_id": "2ef1a5c0752085d3a6935132ad9e597c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" + "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" }, { "type": "NarrativeText", diff --git a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/recalibrating-risk-report.pdf.json b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/recalibrating-risk-report.pdf.json index 3eaa5e3f88..6879697f80 100644 --- a/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/recalibrating-risk-report.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/pdf-fast-reprocess/s3/small-pdf-set/recalibrating-risk-report.pdf.json @@ -141,233 +141,233 @@ }, { "type": "Title", - "element_id": "d977fff4c69c437aa4a44a5c5f4bf02e", + "element_id": "4d7c9c95f808a09f6b0bcfe8b255e537", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Rank Order Laypersons" + "text": "Figure 1. Ordering of perceived risks for 30 activities and technologies1,iii" }, { "type": "Title", - "element_id": "5e12750596bdf1413e64c24997479b21", + "element_id": "d977fff4c69c437aa4a44a5c5f4bf02e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Experts" + "text": "Rank Order Laypersons" }, { "type": "UncategorizedText", - "element_id": "6b86b273ff34fce19d6b804eff5a3f57", + "element_id": "4523540f1504cd17100c4835e85b7eef", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "1" + "text": "17" }, { - "type": "Title", - "element_id": "82a60569029ed9032f1b08891e8524c2", + "type": "UncategorizedText", + "element_id": "785f3ec7eb32f30b90cd0fcf3657d388", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Nuclear power" + "text": "22" }, { "type": "UncategorizedText", - "element_id": "f5ca38f748a1d6eaf726b8a42fb575c3", + "element_id": "624b60c58c9d8bfb6ff1886c2fd605d2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "20" + "text": "30" }, { "type": "UncategorizedText", - "element_id": "d4735e3a265e16eee03f59718b9b5d03", + "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "2" + "text": "" }, { - "type": "Title", - "element_id": "602d25f25cca4ebb709f8b48f54d99d9", + "type": "UncategorizedText", + "element_id": "4b227777d4dd1fc61c6f884f48641d02", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Motor vehicles" + "text": "4" }, { "type": "UncategorizedText", - "element_id": "6b86b273ff34fce19d6b804eff5a3f57", + "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "1" + "text": "" }, { "type": "UncategorizedText", - "element_id": "4e07408562bedb8b60ce05c1decfe3ad", + "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "3" + "text": "" }, { - "type": "Title", - "element_id": "f8e3740e358309bd0570d4f3ca141793", + "type": "UncategorizedText", + "element_id": "d4735e3a265e16eee03f59718b9b5d03", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Handguns" + "text": "2" }, { "type": "UncategorizedText", - "element_id": "4b227777d4dd1fc61c6f884f48641d02", + "element_id": "6b86b273ff34fce19d6b804eff5a3f57", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "4" + "text": "1" }, { "type": "UncategorizedText", - "element_id": "4b227777d4dd1fc61c6f884f48641d02", + "element_id": "4e07408562bedb8b60ce05c1decfe3ad", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "4" + "text": "3" }, { "type": "Title", - "element_id": "eda8f72476c539920d2c0e3515ba4b07", + "element_id": "1656c455012b016fbac5eac0a38397bd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Smoking" + "text": "Electric power (non-nuclear)" }, { - "type": "UncategorizedText", - "element_id": "d4735e3a265e16eee03f59718b9b5d03", + "type": "Title", + "element_id": "602d25f25cca4ebb709f8b48f54d99d9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "2" + "text": "Motor vehicles" }, { - "type": "UncategorizedText", - "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", + "type": "Title", + "element_id": "eda8f72476c539920d2c0e3515ba4b07", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "Smoking" }, { - "type": "UncategorizedText", - "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", + "type": "Title", + "element_id": "2f3122790ccc9e095abe1b5ceedddf88", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "X-rays" }, { - "type": "UncategorizedText", - "element_id": "4523540f1504cd17100c4835e85b7eef", + "type": "Title", + "element_id": "ed3861e631428b9b77e2bdc0384d2cbe", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "17" + "text": "Vaccinations" }, { "type": "Title", - "element_id": "1656c455012b016fbac5eac0a38397bd", + "element_id": "82a60569029ed9032f1b08891e8524c2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Electric power (non-nuclear)" + "text": "Nuclear power" }, { - "type": "UncategorizedText", - "element_id": "19581e27de7ced00ff1ce50b2047e7a5", + "type": "Title", + "element_id": "f8e3740e358309bd0570d4f3ca141793", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "9" + "text": "Handguns" }, { - "type": "UncategorizedText", - "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", + "type": "Title", + "element_id": "5e12750596bdf1413e64c24997479b21", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "Experts" }, { "type": "UncategorizedText", - "element_id": "d1429f8178a04f7fc73a66edf10ab8b5", + "element_id": "b7a56873cd771f2c446d369b649430b6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - 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"type": "Title", - "element_id": "f83714d89302473e0e4f5399bd50e7a9", + "type": "UncategorizedText", + "element_id": "e629fa6598d732768f7c726b4b621285", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "W T" + "text": "15" }, { "type": "NarrativeText", @@ -650,44 +650,44 @@ "text": "r e p s e i t i l" }, { - "type": "UncategorizedText", - "element_id": "4a44dc15364204a80fe80e9039455cc1", + "type": "Title", + "element_id": "1fb2ec4fc8fc547c0de86ba79ba651e5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "10" + "text": "a t a F" }, { "type": "UncategorizedText", - "element_id": "8bf40d0515e8461bd30866c2eb8ac250", + "element_id": "4a44dc15364204a80fe80e9039455cc1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "4.6" + "text": "10" }, { - "type": "Title", - "element_id": "1fb2ec4fc8fc547c0de86ba79ba651e5", + "type": "UncategorizedText", + "element_id": "ef2d127de37b942baad06145e54b0c61", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "a t a F" + "text": "5" }, { "type": "UncategorizedText", - "element_id": "ef2d127de37b942baad06145e54b0c61", + "element_id": "8bf40d0515e8461bd30866c2eb8ac250", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "5" + "text": "4.6" }, { "type": "UncategorizedText", @@ -701,123 +701,123 @@ }, { "type": "UncategorizedText", - "element_id": "91539d7445b231b3612c4f68bd077160", + "element_id": "5feceb66ffc86f38d952786c6d696c79", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0.07" + "text": "0" }, { - "type": "UncategorizedText", - "element_id": "a888fe9e2469182b8e3e3bca241d3189", + "type": "Title", + "element_id": "6c25ebfc9ffd2510c4c41d4bd5cb7ea9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0.04" + "text": "C oal" }, { - "type": "UncategorizedText", - "element_id": "a7e46abf169710b34fe8898b950d57ec", + "type": "Title", + "element_id": "2378bdd2cf4f491cf401e6b215cbb4fd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - 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"text": "Oil" + "text": "Wind" }, { - "type": "Title", - "element_id": "3a21fb0158c2ea04834163deee74a836", + "type": "UncategorizedText", + "element_id": "a888fe9e2469182b8e3e3bca241d3189", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "Bio m ass" + "text": "0.04" }, { - "type": "Title", - "element_id": "4fabb98454d019811a732c4a09f31bf0", + "type": "NarrativeText", + "element_id": "5275a384f63ded9bf8541f52dec2c2cb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "N atural gas" + "text": "H ydropo w er" }, { - "type": "Title", - "element_id": "d151346fe7eea3c6a0865199579ca601", + "type": "UncategorizedText", + "element_id": "a7e46abf169710b34fe8898b950d57ec", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "Wind" + "text": "0.02" }, { - "type": "NarrativeText", - "element_id": "5275a384f63ded9bf8541f52dec2c2cb", + "type": "Title", + "element_id": "d3d1de6bcd7ebe2351be9f53551f7eb9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "H ydropo w er" + "text": "S olar" }, { - "type": "Title", - "element_id": "d3d1de6bcd7ebe2351be9f53551f7eb9", + "type": "UncategorizedText", + "element_id": "312b95ee5a344d2f7a16ad817ff70788", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "S olar" + "text": "0.01" }, { "type": "Title", @@ -990,34 +990,34 @@ "text": "If the potential of nuclear energy is to be fully realized, public health and safety approaches must be recalibrated to consider a wider range of factors when considering radiation, adopting an “all-hazards” approach. Such an approach must ensure that risks are placed within a proper perspective and context, rather than looking at them in isolation. We therefore must not look at the costs – be they economic, environmental, or public health – associated with an individual power plant in isolation, but rather the costs associated with it (and its alternatives) at a societal level (Figure 4). This would entail looking at the potential risks arising from the use of nuclear power and comparing these with the risks associated with not adopting nuclear power." }, { - "type": "UncategorizedText", - "element_id": "fd38688f30f8b6e597d540ab0134278f", + "type": "Title", + "element_id": "2470c376b60fd11fd9639e0e440ce0f5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Social and environmental costs of emissions, land-use, climate change, security of supply, etc." + "text": "Plant-level production costs at market prices" }, { "type": "Title", - "element_id": "2470c376b60fd11fd9639e0e440ce0f5", + "element_id": "dde91891334d5ac0e2b4569680eb6f1e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Plant-level production costs at market prices" + "text": "Grid-level costs of the electricity system" }, { - "type": "Title", - "element_id": "dde91891334d5ac0e2b4569680eb6f1e", + "type": "UncategorizedText", + "element_id": "fd38688f30f8b6e597d540ab0134278f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Grid-level costs of the electricity system" + "text": "Social and environmental costs of emissions, land-use, climate change, security of supply, etc." }, { "type": "NarrativeText", @@ -1410,24 +1410,24 @@ "text": "8" }, { - "type": "Title", - "element_id": "2ef1a5c0752085d3a6935132ad9e597c", + "type": "UncategorizedText", + "element_id": "481e5a54650b0a4ac7bc2568ddad436d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" + "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" }, { - "type": "UncategorizedText", - "element_id": "481e5a54650b0a4ac7bc2568ddad436d", + "type": "Title", + "element_id": "2ef1a5c0752085d3a6935132ad9e597c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" + "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" }, { "type": "NarrativeText", diff --git a/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json b/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json index 89ce864c3c..4ef6219df6 100644 --- a/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/2023-Jan-economic-outlook.pdf.json @@ -151,253 +151,253 @@ }, { "type": "UncategorizedText", - "element_id": "46e79d62a98bd3d789932f6067e287f9", + "element_id": "57fc9bcaeb3e10af7c346784ab265262", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Median country Brazil" + "text": "18 16 14 12 10 8 6 4 2 0 –2" }, { "type": "UncategorizedText", - "element_id": "884129b7691d98f541650f9974a03432", + "element_id": "c620a5b5b4db7227ec57c4de63d5705a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "United States" + "text": "–2" }, { "type": "UncategorizedText", - "element_id": "f6c3fd5799c2eef312a23fc38f106b71", + "element_id": "42954d589ec9936c27951193ea1a0055", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Euro area" + "text": "16 14 12 10 8 6 4 2 0" }, { "type": "UncategorizedText", - "element_id": "57fc9bcaeb3e10af7c346784ab265262", + "element_id": "982a4e27ceee8ebea442a9e655d514a2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "18 16 14 12 10 8 6 4 2 0 –2" + "text": "Jan. 2019" }, { "type": "UncategorizedText", - "element_id": "4615380b5cffb82f6b9c5e2dd6459757", + "element_id": "982a4e27ceee8ebea442a9e655d514a2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "1. Headline Inflation" + "text": "Jan. 2019" }, { "type": "UncategorizedText", - "element_id": "982a4e27ceee8ebea442a9e655d514a2", + "element_id": "4615380b5cffb82f6b9c5e2dd6459757", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 2019" + "text": "1. Headline Inflation" }, { "type": "UncategorizedText", - "element_id": "977d74af7626f2abfd2ac76999c2b532", + "element_id": "f71f3bada3b49736b1a8857b091c9415", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 19" + "text": "2. Core Inflation" }, { "type": "UncategorizedText", - "element_id": "b02dddf9e55f98d11d6f969e781256c7", + "element_id": "46e79d62a98bd3d789932f6067e287f9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 20" + "text": "Median country Brazil" }, { "type": "UncategorizedText", - "element_id": "44ea2235bcfba828c66c9e07ae9de9ab", + "element_id": "977d74af7626f2abfd2ac76999c2b532", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 20" + "text": "Jul. 19" }, { "type": "UncategorizedText", - "element_id": "5abf188738ee99991cae53cd3942588b", + "element_id": "977d74af7626f2abfd2ac76999c2b532", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 21" + "text": "Jul. 19" }, { "type": "UncategorizedText", - "element_id": "18f1504e5633185fe4f66dc0215c7e0f", + "element_id": "b02dddf9e55f98d11d6f969e781256c7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 21" + "text": "Jan. 20" }, { "type": "UncategorizedText", - "element_id": "d5190b32fd3af45c0dc1599725380144", + "element_id": "b02dddf9e55f98d11d6f969e781256c7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 22" + "text": "Jan. 20" }, { "type": "UncategorizedText", - "element_id": "5b7e9f3b7b7e91b3cb4e6195c1f36d25", + "element_id": "44ea2235bcfba828c66c9e07ae9de9ab", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 22" + "text": "Jul. 20" }, { "type": "UncategorizedText", - "element_id": "ecd9703cc08fd1fb525673b558111d7b", + "element_id": "44ea2235bcfba828c66c9e07ae9de9ab", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Nov. 22" + "text": "Jul. 20" }, { "type": "UncategorizedText", - "element_id": "42954d589ec9936c27951193ea1a0055", + "element_id": "884129b7691d98f541650f9974a03432", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "16 14 12 10 8 6 4 2 0" + "text": "United States" }, { "type": "UncategorizedText", - "element_id": "f71f3bada3b49736b1a8857b091c9415", + "element_id": "5abf188738ee99991cae53cd3942588b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "2. Core Inflation" + "text": "Jan. 21" }, { "type": "UncategorizedText", - "element_id": "c620a5b5b4db7227ec57c4de63d5705a", + "element_id": "5abf188738ee99991cae53cd3942588b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "–2" + "text": "Jan. 21" }, { "type": "UncategorizedText", - "element_id": "982a4e27ceee8ebea442a9e655d514a2", + "element_id": "18f1504e5633185fe4f66dc0215c7e0f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 2019" + "text": "Jul. 21" }, { "type": "UncategorizedText", - "element_id": "977d74af7626f2abfd2ac76999c2b532", + "element_id": "18f1504e5633185fe4f66dc0215c7e0f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 19" + "text": "Jul. 21" }, { "type": "UncategorizedText", - "element_id": "b02dddf9e55f98d11d6f969e781256c7", + "element_id": "f6c3fd5799c2eef312a23fc38f106b71", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 20" + "text": "Euro area" }, { "type": "UncategorizedText", - "element_id": "44ea2235bcfba828c66c9e07ae9de9ab", + "element_id": "d5190b32fd3af45c0dc1599725380144", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 20" + "text": "Jan. 22" }, { "type": "UncategorizedText", - "element_id": "5abf188738ee99991cae53cd3942588b", + "element_id": "d5190b32fd3af45c0dc1599725380144", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 21" + "text": "Jan. 22" }, { "type": "UncategorizedText", - "element_id": "18f1504e5633185fe4f66dc0215c7e0f", + "element_id": "5b7e9f3b7b7e91b3cb4e6195c1f36d25", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 21" + "text": "Jul. 22" }, { "type": "UncategorizedText", - "element_id": "d5190b32fd3af45c0dc1599725380144", + "element_id": "5b7e9f3b7b7e91b3cb4e6195c1f36d25", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jan. 22" + "text": "Jul. 22" }, { "type": "UncategorizedText", - "element_id": "5b7e9f3b7b7e91b3cb4e6195c1f36d25", + "element_id": "ecd9703cc08fd1fb525673b558111d7b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 3 }, - "text": "Jul. 22" + "text": "Nov. 22" }, { "type": "UncategorizedText", @@ -661,23 +661,23 @@ }, { "type": "NarrativeText", - "element_id": "d24af8f44bd419665bb4ab6efef34fed", + "element_id": "72d289ea524eebcd8f195a8afda1c223", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "About 84 percent of countries are expected to have lower headline (consumer price index) inflation in 2023 than in 2022. Global inflation is set to fall from 8.8 percent in 2022 (annual average) to 6.6 percent in 2023 and 4.3 percent in 2024––above pre-pandemic (2017–19) levels of about 3.5 percent. The projected disinflation partly reflects declining international fuel and nonfuel commodity prices due to weaker global demand. It also reflects the cooling effects of monetary policy tightening on underlying (core) inflation, which globally is expected to decline from 6.9 percent in the fourth quarter of 2022 (year over year) to 4.5 percent by the fourth quarter of 2023. Still, disinflation will take time: by 2024, projected annual average headline and core inflation will, respectively, still be above pre-pandemic levels in 82 percent and 86 percent of economies." + "text": "In advanced economies, annual average inflation is projected to decline from 7.3 percent in 2022 to 4.6 percent in 2023 and 2.6 percent in 2024––above target in several cases. In emerging market and developing economies, projected annual inflation declines from 9.9 percent in 2022 to 8.1 percent in 2023 and 5.5 percent in 2024, above the 4.9 percent pre-pandemic (2017–19) average. In low-income developing countries, inflation is projected to moderate from 14.2 percent in 2022 to 8.6 percent in 2024––still high, but close to the pre-pandemic average." }, { "type": "NarrativeText", - "element_id": "72d289ea524eebcd8f195a8afda1c223", + "element_id": "d24af8f44bd419665bb4ab6efef34fed", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 6 }, - "text": "In advanced economies, annual average inflation is projected to decline from 7.3 percent in 2022 to 4.6 percent in 2023 and 2.6 percent in 2024––above target in several cases. In emerging market and developing economies, projected annual inflation declines from 9.9 percent in 2022 to 8.1 percent in 2023 and 5.5 percent in 2024, above the 4.9 percent pre-pandemic (2017–19) average. In low-income developing countries, inflation is projected to moderate from 14.2 percent in 2022 to 8.6 percent in 2024––still high, but close to the pre-pandemic average." + "text": "About 84 percent of countries are expected to have lower headline (consumer price index) inflation in 2023 than in 2022. Global inflation is set to fall from 8.8 percent in 2022 (annual average) to 6.6 percent in 2023 and 4.3 percent in 2024––above pre-pandemic (2017–19) levels of about 3.5 percent. The projected disinflation partly reflects declining international fuel and nonfuel commodity prices due to weaker global demand. It also reflects the cooling effects of monetary policy tightening on underlying (core) inflation, which globally is expected to decline from 6.9 percent in the fourth quarter of 2022 (year over year) to 4.5 percent by the fourth quarter of 2023. Still, disinflation will take time: by 2024, projected annual average headline and core inflation will, respectively, still be above pre-pandemic levels in 82 percent and 86 percent of economies." }, { "type": "Title", @@ -710,734 +710,734 @@ "text": "Table 1. Overview of the World Economic Outlook Projections (Percent change, unless noted otherwise)" }, { - "type": "UncategorizedText", - "element_id": "0e4a5b1f1ad9e749a679128c0640bd3f", + "type": "Table", + "element_id": "63bdc79def2500227001ac95d78727ab", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Year over Year" + "text": "Difference from October 2022 Q4 over Q4 2/ Estimate___ Projections WEO Projections 1/ Estimate Projections 2021 2022 2023 2024 2023 2024 2022 2023 2024 World Output 6.2 34 29 34 0.2 0.1 1.9 3.2 3.0 Advanced Economies 5.4 27 1.2 14 04 0.2 1.3 14 1.6 United States 5.9 2.0 14 1.0 04 -0.2 07 1.0 13 Euro Area 5.3 3.5 07 16 0.2 -0.2 19 0.5 24 Germany 26 19 01 14 04 0.1 14 0.0 23 France 68 26 07 16 0.0 0.0 0.5 09 18 Italy 67 3.9 06 0.9 08 -04 21 0.1 1.0 Spain 5.5 5.2 14 24 -0.1 -0.2 21 13 28 Japan 21 14 18 0.9 0.2 -04 17 1.0 1.0 United Kingdom 76 41 -06 0.9 -0.9 03 04 -05 18 Canada 5.0 3.5 15 15 0.0 0.1 23 12 1.9 Other Advanced Economies 3/ 5.3 28 20 24 -03 02 14 2a 2.2 Emerging Market and Developing Economies 67 3.9 40 42 0.3 -0.1 25 5.0 4A Emerging and Developing Asia 74 43 5.3 5.2 04 0.0 3.4 6.2 49 China 84 3.0 5.2 45 08 0.0 29 5.9 41 India 4/ 87 68 61 68 0.0 0.0 43 70 7A Emerging and Developing Europe 69 07 15 26 0.9 01 -2.0 3.5 28 Russia 47 -2.2 0.3 21 26 06 441 1.0 2.0 Latin America and the Caribbean 7.0 3.9 18 2a 04 0.3 26 1.9 19 Brazil 5.0 34 12 15 0.2 -04 28 0.8 22 Mexico 47 34 47 16 05 -0.2 37 14 1.9 Middle East and Central Asia 45 5.3 3.2 37 -04 0.2 . . . Saudi Arabia 3.2 87 26 34 -11 0.5 46 27 35 Sub-Saharan Africa 47 38 38 41 04 0.0 = ao ao Nigeria 3.6 3.0 3.2 29 0.2 0.0 26 31 29 South Africa 49 26 12 13 01 0.0 3.0 0.5 18 Memorandum World Growth Based on Market Exchange Rates 6.0 3.41 24 25 03 -0.1 17 25 25 European Union 5.5 37 07 18 0.0 -0.3 18 1.2 2.0 ASEAN-5 5/ 3.8 5.2 43 47 0.2 -0.2 37 57 40 Middle East and North Africa 41 54 3.2 35 -04 0.2 a . . Emerging Market and Middle-Income Economies 70 38 40 44 04 0.0 25 5.0 44 Low-Income Developing Countries 441 49 49 56 0.0 01 World Trade Volume (goods and services) 6/ 10.4 5.4 24 3.4 -01 -0.3 Advanced Economies 94 66 23 27 0.0 -04 Emerging Market and Developing Economies 124 34 26 46 03 0.0 Commodity Prices Oil 7/ 65.8 39.8 -16.2 71 33 -0.9 11.2 -98 59 Nonfuel (average based on world commodity import weights) 26.4 70 -6.3 -0.4 -01 03 -2.0 14 -0.2 World Consumer Prices 8/ 47 88 6.6 43 04 0.2 9.2 5.0 3.5 Advanced Economies 9/ 34 73 46 26 0.2 02 78 31 23 Emerging Market and Developing Economies 8/ 5.9 99 84 5.5 0.0 02 10.4 66 45," }, { - "type": "Table", - "element_id": "63bdc79def2500227001ac95d78727ab", + "type": "UncategorizedText", + "element_id": "df04e6bab0287bf91974bb7bd5735177", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Difference from October 2022 Q4 over Q4 2/ Estimate___ Projections WEO Projections 1/ Estimate Projections 2021 2022 2023 2024 2023 2024 2022 2023 2024 World Output 6.2 34 29 34 0.2 0.1 1.9 3.2 3.0 Advanced Economies 5.4 27 1.2 14 04 0.2 1.3 14 1.6 United States 5.9 2.0 14 1.0 04 -0.2 07 1.0 13 Euro Area 5.3 3.5 07 16 0.2 -0.2 19 0.5 24 Germany 26 19 01 14 04 0.1 14 0.0 23 France 68 26 07 16 0.0 0.0 0.5 09 18 Italy 67 3.9 06 0.9 08 -04 21 0.1 1.0 Spain 5.5 5.2 14 24 -0.1 -0.2 21 13 28 Japan 21 14 18 0.9 0.2 -04 17 1.0 1.0 United Kingdom 76 41 -06 0.9 -0.9 03 04 -05 18 Canada 5.0 3.5 15 15 0.0 0.1 23 12 1.9 Other Advanced Economies 3/ 5.3 28 20 24 -03 02 14 2a 2.2 Emerging Market and Developing Economies 67 3.9 40 42 0.3 -0.1 25 5.0 4A Emerging and Developing Asia 74 43 5.3 5.2 04 0.0 3.4 6.2 49 China 84 3.0 5.2 45 08 0.0 29 5.9 41 India 4/ 87 68 61 68 0.0 0.0 43 70 7A Emerging and Developing Europe 69 07 15 26 0.9 01 -2.0 3.5 28 Russia 47 -2.2 0.3 21 26 06 441 1.0 2.0 Latin America and the Caribbean 7.0 3.9 18 2a 04 0.3 26 1.9 19 Brazil 5.0 34 12 15 0.2 -04 28 0.8 22 Mexico 47 34 47 16 05 -0.2 37 14 1.9 Middle East and Central Asia 45 5.3 3.2 37 -04 0.2 . . . Saudi Arabia 3.2 87 26 34 -11 0.5 46 27 35 Sub-Saharan Africa 47 38 38 41 04 0.0 = ao ao Nigeria 3.6 3.0 3.2 29 0.2 0.0 26 31 29 South Africa 49 26 12 13 01 0.0 3.0 0.5 18 Memorandum World Growth Based on Market Exchange Rates 6.0 3.41 24 25 03 -0.1 17 25 25 European Union 5.5 37 07 18 0.0 -0.3 18 1.2 2.0 ASEAN-5 5/ 3.8 5.2 43 47 0.2 -0.2 37 57 40 Middle East and North Africa 41 54 3.2 35 -04 0.2 a . . Emerging Market and Middle-Income Economies 70 38 40 44 04 0.0 25 5.0 44 Low-Income Developing Countries 441 49 49 56 0.0 01 World Trade Volume (goods and services) 6/ 10.4 5.4 24 3.4 -01 -0.3 Advanced Economies 94 66 23 27 0.0 -04 Emerging Market and Developing Economies 124 34 26 46 03 0.0 Commodity Prices Oil 7/ 65.8 39.8 -16.2 71 33 -0.9 11.2 -98 59 Nonfuel (average based on world commodity import weights) 26.4 70 -6.3 -0.4 -01 03 -2.0 14 -0.2 World Consumer Prices 8/ 47 88 6.6 43 04 0.2 9.2 5.0 3.5 Advanced Economies 9/ 34 73 46 26 0.2 02 78 31 23 Emerging Market and Developing Economies 8/ 5.9 99 84 5.5 0.0 02 10.4 66 45," + "text": "Commodity Prices Oil 7/ Nonfuel (average based on world commodity import weights)" }, { "type": "UncategorizedText", - "element_id": "a818ed93ce57d385096f12f5c767b245", + "element_id": "528d8d2d6956ed52388c4fd81efe4d90", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Difference from October 2022" + "text": "World Output" }, { "type": "UncategorizedText", - "element_id": "82c898f5486c8a1e3cc07db6d38f3281", + "element_id": "98dd3f393c886d9c6f711eadb942fcc3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Q4 over Q4 2/" + "text": "World Trade Volume (goods and services) 6/ Advanced Economies Emerging Market and Developing Economies" }, { "type": "UncategorizedText", - "element_id": "9fadcec06728c082b131a193fd30b687", + "element_id": "30d3d3727ce2a10ca83af5fb8b2caeb5", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "WEO Projections 1/" + "text": "World Consumer Prices 8/ Advanced Economies 9/ Emerging Market and Developing Economies 8/" }, { "type": "UncategorizedText", - "element_id": "f9e434990230ffa44a7228127daa3f7a", + "element_id": "9125c7c4a007ad95a0ea2328a61481e2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Estimate 2022" + "text": "Emerging and Developing Europe" }, { "type": "UncategorizedText", - "element_id": "7007d8379a7cec938d222daa3ebaf5ba", + "element_id": "2aaf1fdc5675c7dc6c4a04d2ad50dfc9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Projections 2023" + "text": "Advanced Economies United States Euro Area" }, { "type": "UncategorizedText", - "element_id": "f9e434990230ffa44a7228127daa3f7a", + "element_id": "04ecb0bb1325f828a0d1ae1a6b639c2f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Estimate 2022" + "text": "Memorandum World Growth Based on Market Exchange Rates European Union ASEAN-5 5/ Middle East and North Africa Emerging Market and Middle-Income Economies Low-Income Developing Countries" }, { "type": "UncategorizedText", - "element_id": "7007d8379a7cec938d222daa3ebaf5ba", + "element_id": "d3651b0ff5fd7f4dc6e946418ff72ed9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Projections 2023" + "text": "Japan United Kingdom Canada Other Advanced Economies 3/" }, { "type": "UncategorizedText", - "element_id": "2b05abac83ad534cb6c39d58f8516e93", + "element_id": "20f5efc45d2f76e4b28389cfb4427fb8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2021" + "text": "Saudi Arabia Sub-Saharan Africa" }, { "type": "UncategorizedText", - "element_id": "f1c54cd860f2a7dfaf6d5e9cda3628d6", + "element_id": "a005698da5ad176ddd7fcf99f1e72052", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2024" + "text": "Middle East and Central Asia" }, { "type": "UncategorizedText", - "element_id": "c6ca8236fc3e2b7b83a25d15503cf990", + "element_id": "9667705c9b14e33b63121010f690b8f2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2023" + "text": "Emerging Market and Developing Economies Emerging and Developing Asia" }, { "type": "UncategorizedText", - "element_id": "f1c54cd860f2a7dfaf6d5e9cda3628d6", + "element_id": "12629937182fa7dc287c650de98baa7c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2024" + "text": "Latin America and the Caribbean" }, { "type": "UncategorizedText", - "element_id": "f1c54cd860f2a7dfaf6d5e9cda3628d6", + "element_id": "5e994f4f6e6c548cdc7722b87d4ec753", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "2024" + "text": "Nigeria South Africa" }, { "type": "UncategorizedText", - "element_id": "528d8d2d6956ed52388c4fd81efe4d90", + "element_id": "70b4c09224e2558081a9777119bc5e95", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "World Output" + "text": "Brazil Mexico" }, { "type": "UncategorizedText", - "element_id": "e18fc7615777b155357a9245de518953", + "element_id": "8bb55ecb597cb314ebe018e1eb2012f3", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "6.2" + "text": "Germany France Italy Spain" }, { "type": "UncategorizedText", - "element_id": "fccdd069c043aa4c86036517c99c80b9", + "element_id": "d366b7da298b208d406559e07737e49c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - 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"text": "–16.2 –6.3" + "text": "Q4 over Q4 2/" }, { "type": "UncategorizedText", - "element_id": "edbd6e6ed3e9bad033a255abcf843688", + "element_id": "7007d8379a7cec938d222daa3ebaf5ba", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "–7.1 –0.4" + "text": "Projections 2023" }, { "type": "UncategorizedText", - "element_id": "6095b96ddfd471fdd827fc57191deac7", + "element_id": "d59544246991b3f4c7f2b3eb0fe55aa2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "–3.3 –0.1" + "text": "–9.8 1.4" }, { "type": "UncategorizedText", - "element_id": "80dcbb0dc10d8c1c50d9abaca086b5b6", + "element_id": "15507d77d6f083ad0469a5b27c7a97eb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "–0.9 0.3" + "text": "1.1 1.0 0.5 0.0 0.9 0.1 1.3 1.0 –0.5 1.2 2.1" }, { "type": "UncategorizedText", - "element_id": "aa03ccf072c1540515836879196279f4", + "element_id": "73356c80e67292eab1403c43e9bbb6fa", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "11.2 –2.0" + "text": ". . . . . . . . ." }, { "type": "UncategorizedText", - "element_id": "d59544246991b3f4c7f2b3eb0fe55aa2", + "element_id": "2ebea8c404fdbf0f73f7190810d22cf8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "–9.8 1.4" + "text": "5.0 3.1 6.6" }, { "type": "UncategorizedText", - "element_id": "a7cdd10df545635ab3a8515dbaaff720", + "element_id": "56010fa3453e21765ccdf5076960ad2c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "–5.9 –0.2" + "text": "3.2" }, { "type": "UncategorizedText", - "element_id": "30d3d3727ce2a10ca83af5fb8b2caeb5", + "element_id": "bdcf83d42c2f79ce5b532b91ece15d53", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "World Consumer Prices 8/ Advanced Economies 9/ Emerging Market and Developing Economies 8/" + "text": "2.5 1.2 5.7 . . . 5.0 . . ." }, { "type": "UncategorizedText", - "element_id": "d75e0ba5451cc12f775ec3e84d5a6c4f", + "element_id": "40696241a92836702680491eb3d6f31d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "4.7 3.1 5.9" + "text": "5.0 6.2 5.9 7.0 3.5 1.0 1.9 0.8 1.1 . . . 2.7 . . . 3.1 0.5" }, { "type": "UncategorizedText", - "element_id": "b6bf373cba13ecb49fa2a76e42bfaa4f", + "element_id": "f1c54cd860f2a7dfaf6d5e9cda3628d6", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "8.8 7.3 9.9" + "text": "2024" }, { "type": "UncategorizedText", - "element_id": "adbebe93f3dd02702155f1137d795bee", + "element_id": "a7cdd10df545635ab3a8515dbaaff720", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "6.6 4.6 8.1" + "text": "–5.9 –0.2" }, { "type": "UncategorizedText", - "element_id": "7a6c52054e3d9f1c73382beea1f72b0d", + "element_id": "df7318d8afd930b2f2049127f4e90e0e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "4.3 2.6 5.5" + "text": "3.5 2.3 4.5" }, { "type": "UncategorizedText", - "element_id": "8c13bb021ca9e565a46bd959bd859a46", + "element_id": "82eb710aeec934b729906546268a7087", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "0.1 0.2 0.0" + "text": "3.0" }, { "type": "UncategorizedText", - "element_id": "b6fde97f086a68c8a6bb3fc15077bd05", + "element_id": "97b19eab144ecd45afce13280ebf73f0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "0.2 0.2 0.2" + "text": "4.1 4.9 4.1 7.1 2.8 2.0 1.9 2.2 1.9 . . . 3.5 . . . 2.9 1.8" }, { "type": "UncategorizedText", - "element_id": "9e0af8006c1b96c35937f0d08d85711d", + "element_id": "73356c80e67292eab1403c43e9bbb6fa", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "9.2 7.8 10.4" + "text": ". . . . . . . . ." }, { "type": "UncategorizedText", - "element_id": "2ebea8c404fdbf0f73f7190810d22cf8", + "element_id": "15e586af718d7b1b04fc8fb83f83f814", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "5.0 3.1 6.6" + "text": "1.6 1.3 2.1 2.3 1.8 1.0 2.8 1.0 1.8 1.9 2.2" }, { "type": "UncategorizedText", - "element_id": "df7318d8afd930b2f2049127f4e90e0e", + "element_id": "54add9deb165bffe2c1e635146114e1d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "3.5 2.3 4.5" + "text": "2.5 2.0 4.0 . . . 4.1 . . ." }, { "type": "NarrativeText", - "element_id": "dd295fca8aff81058c48312a022b69b2", + "element_id": "df59a495ef85c5f70c5ba5356caf764a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Note: Real effective exchange rates are assumed to remain constant at the levels prevailing during October 26, 2022--November 23, 2022. Economies are listed on the basis of economic size. The aggregated quarterly data are seasonally adjusted. WEO = World Economic Outlook. 1/ Difference based on rounded figures for the current and October 2022 WEO forecasts. Countries whose forecasts have been updated relative to October 2022 WEO forecasts account for approximately 90 percent of world GDP measured at purchasing-power-parity weights. 2/ For World Output (Emerging Market and Developing Economies), the quarterly estimates and projections account for approximately 90 percent (80 percent) of annual world (emerging market and developing economies') output at purchasing-power-parity weights. 3/ Excludes the Group of Seven (Canada, France, Germany, Italy, Japan, United Kingdom, United States) and euro area countries. 4/ For India, data and projections are presented on a fiscal year basis, with FY 2022/23 (starting in April 2022) shown in the 2022 column. India's growth projections are 5.4 percent in 2023 and 6.8 percent in 2024 based on calendar year. 5/ Indonesia, Malaysia, Philippines, Singapore, Thailand. 6/ Simple average of growth rates for export and import volumes (goods and services). 7/ Simple average of prices of UK Brent, Dubai Fateh, and West Texas Intermediate crude oil. The average assumed price of oil in US dollars a barrel, based on futures markets (as of November 29, 2022), is $81.13 in 2023 and $75.36 in 2024. 8/ Excludes Venezuela. 9/ The inflation rate for the euro area is 5.7% in 2023 and 3.3% in 2024, that for Japan is 2.8% in 2023 and 2.0% in 2024, and that for the United States is 4.0% in 2023 and 2.2% in 2024." + "text": "Upside risks—Plausible upside risks include more favorable surprises to domestic spending—as in the third quarter of 2022—which, however, would increase inflation further. At the same time, there is room for an upside scenario with lower-than-expected inflation and less monetary tightening:" }, { "type": "NarrativeText", - "element_id": "df59a495ef85c5f70c5ba5356caf764a", + "element_id": "dd295fca8aff81058c48312a022b69b2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Upside risks—Plausible upside risks include more favorable surprises to domestic spending—as in the third quarter of 2022—which, however, would increase inflation further. At the same time, there is room for an upside scenario with lower-than-expected inflation and less monetary tightening:" + "text": "Note: Real effective exchange rates are assumed to remain constant at the levels prevailing during October 26, 2022--November 23, 2022. Economies are listed on the basis of economic size. The aggregated quarterly data are seasonally adjusted. WEO = World Economic Outlook. 1/ Difference based on rounded figures for the current and October 2022 WEO forecasts. Countries whose forecasts have been updated relative to October 2022 WEO forecasts account for approximately 90 percent of world GDP measured at purchasing-power-parity weights. 2/ For World Output (Emerging Market and Developing Economies), the quarterly estimates and projections account for approximately 90 percent (80 percent) of annual world (emerging market and developing economies') output at purchasing-power-parity weights. 3/ Excludes the Group of Seven (Canada, France, Germany, Italy, Japan, United Kingdom, United States) and euro area countries. 4/ For India, data and projections are presented on a fiscal year basis, with FY 2022/23 (starting in April 2022) shown in the 2022 column. India's growth projections are 5.4 percent in 2023 and 6.8 percent in 2024 based on calendar year. 5/ Indonesia, Malaysia, Philippines, Singapore, Thailand. 6/ Simple average of growth rates for export and import volumes (goods and services). 7/ Simple average of prices of UK Brent, Dubai Fateh, and West Texas Intermediate crude oil. The average assumed price of oil in US dollars a barrel, based on futures markets (as of November 29, 2022), is $81.13 in 2023 and $75.36 in 2024. 8/ Excludes Venezuela. 9/ The inflation rate for the euro area is 5.7% in 2023 and 3.3% in 2024, that for Japan is 2.8% in 2023 and 2.0% in 2024, and that for the United States is 4.0% in 2023 and 2.2% in 2024." }, { "type": "UncategorizedText", @@ -1760,24 +1760,24 @@ "text": " China’s recovery stalling: Amid still-low population immunity levels and insufficient hospital" }, { - "type": "NarrativeText", - "element_id": "1bbcee85386321e6e8235a64d4c34d73", + "type": "UncategorizedText", + "element_id": "61f61f085d5129c6be48c8bc026c813d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "capacity, especially outside the major urban areas, significant health consequences could hamper the recovery. A deepening crisis in the real estate market remains a major source of vulnerability, with risks of widespread defaults by developers and resulting financial sector instability. Spillovers to the rest of the world would operate primarily through lower demand and potentially renewed supply chain problems." + "text": " War in Ukraine escalating: An escalation of the war in Ukraine remains a major source of" }, { - "type": "UncategorizedText", - "element_id": "61f61f085d5129c6be48c8bc026c813d", + "type": "NarrativeText", + "element_id": "1bbcee85386321e6e8235a64d4c34d73", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": " War in Ukraine escalating: An escalation of the war in Ukraine remains a major source of" + "text": "capacity, especially outside the major urban areas, significant health consequences could hamper the recovery. A deepening crisis in the real estate market remains a major source of vulnerability, with risks of widespread defaults by developers and resulting financial sector instability. Spillovers to the rest of the world would operate primarily through lower demand and potentially renewed supply chain problems." }, { "type": "UncategorizedText", @@ -1950,24 +1950,24 @@ "text": "Strengthening multilateral cooperation—Urgent action is needed to limit the risks stemming from geopolitical fragmentation and to ensure cooperation on fundamental areas of common interest:" }, { - "type": "UncategorizedText", - "element_id": "4aec867d23254666d198ae10167ea5f8", + "type": "NarrativeText", + "element_id": "cb704f1b6d23bfe23f6b4109c471ac8b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": " Restraining the pandemic: Global coordination is needed to resolve bottlenecks in the global" + "text": "distribution of vaccines and treatments. Public support for the development of new vaccine technologies and the design of systematic responses to future epidemics also remains essential.  Addressing debt distress: Progress has been made for countries that requested debt treatment under the Group of Twenty’s Common Framework initiative, and more will be needed to strengthen it. It is also necessary to agree on mechanisms to resolve debt in a broader set of economies, including middle-income countries that are not eligible under the Common Framework. Non– Paris Club and private creditors have a crucial role to play in ensuring coordinated, effective, and timely debt resolution processes." }, { - "type": "NarrativeText", - "element_id": "cb704f1b6d23bfe23f6b4109c471ac8b", + "type": "UncategorizedText", + "element_id": "4aec867d23254666d198ae10167ea5f8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "distribution of vaccines and treatments. Public support for the development of new vaccine technologies and the design of systematic responses to future epidemics also remains essential.  Addressing debt distress: Progress has been made for countries that requested debt treatment under the Group of Twenty’s Common Framework initiative, and more will be needed to strengthen it. It is also necessary to agree on mechanisms to resolve debt in a broader set of economies, including middle-income countries that are not eligible under the Common Framework. Non– Paris Club and private creditors have a crucial role to play in ensuring coordinated, effective, and timely debt resolution processes." + "text": " Restraining the pandemic: Global coordination is needed to resolve bottlenecks in the global" }, { "type": "UncategorizedText", @@ -2021,23 +2021,23 @@ }, { "type": "UncategorizedText", - "element_id": "f79a09409db68af141e82d9ac113ded8", + "element_id": "be54412821e5c5c1d8dd726e2a1518f1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Figure 1.1. Global Financial Conditions: Selected Regions (Standard deviations from mean)" + "text": "Slowing aggregate demand and weaker-than-expected inflation prints in some major advanced economies have prompted investors’ anticipation of a further reduction in the pace of future policy rate hikes. Corporate earnings forecasts have been cut due to headwinds from slowing demand, and margins have contracted across most regions. In addition, survey-based probabilities of recession have been increasing, particularly in the United States and Europe. However, upside risks to the inflation outlook remain. Despite the recent moderation in headline inflation, core inflation remains stubbornly high across most regions, labor markets are still tight, energy prices remain pressured by Russia’s ongoing war in Ukraine, and supply chain disruptions may reappear. To keep these risks in check, financial conditions will likely need to tighten further. If not, central banks may need to increase policy rates even more in order to achieve their inflation objectives." }, { "type": "UncategorizedText", - "element_id": "3bb936c1a0a051d8786700b630295974", + "element_id": "f79a09409db68af141e82d9ac113ded8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "United States Euro area China Other AEs Other EMs" + "text": "Figure 1.1. Global Financial Conditions: Selected Regions (Standard deviations from mean)" }, { "type": "UncategorizedText", @@ -2051,43 +2051,53 @@ }, { "type": "UncategorizedText", - "element_id": "32d9d432ea30d4913ea73770664638a6", + "element_id": "06e9d52c1720fca412803e3b07c4b228", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "October 2022 GFSR" + "text": "6" }, { "type": "UncategorizedText", - "element_id": "06e9d52c1720fca412803e3b07c4b228", + "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "6" + "text": "5" }, { "type": "UncategorizedText", - "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", + "element_id": "7de1555df0c2700329e815b93b32c571", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "5" + "text": "4" }, { "type": "UncategorizedText", - "element_id": "7de1555df0c2700329e815b93b32c571", + "element_id": "3bb936c1a0a051d8786700b630295974", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "4" + "text": "United States Euro area China Other AEs Other EMs" + }, + { + "type": "UncategorizedText", + "element_id": "32d9d432ea30d4913ea73770664638a6", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 11 + }, + "text": "October 2022 GFSR" }, { "type": "UncategorizedText", @@ -2171,73 +2181,73 @@ }, { "type": "UncategorizedText", - "element_id": "dfdb0f123cf8b8b2bb36f70da82b8804", + "element_id": "09249963490d90835afd8926fbb61e62", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "10 10" + "text": "06" }, { "type": "UncategorizedText", - "element_id": "cdcd7da134ed48b36d35843e9f31af03", + "element_id": "dfdb0f123cf8b8b2bb36f70da82b8804", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "12 12" + "text": "10 10" }, { "type": "UncategorizedText", - "element_id": "0ec960fab1d2953e7149d0f3c7024364", + "element_id": "cdcd7da134ed48b36d35843e9f31af03", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "14 16 14" + "text": "12 12" }, { "type": "UncategorizedText", - "element_id": "ea079c2747fa5ebeedffbc53cba88970", + "element_id": "0ec960fab1d2953e7149d0f3c7024364", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "18 18" + "text": "14 16 14" }, { "type": "UncategorizedText", - "element_id": "c233ba96b340d716275a45f83a22708d", + "element_id": "e6c21e8d260fe71882debdb339d2402a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "20 22 22" + "text": "16" }, { "type": "UncategorizedText", - "element_id": "09249963490d90835afd8926fbb61e62", + "element_id": "ea079c2747fa5ebeedffbc53cba88970", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "06" + "text": "18 18" }, { "type": "UncategorizedText", - "element_id": "e6c21e8d260fe71882debdb339d2402a", + "element_id": "c233ba96b340d716275a45f83a22708d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "16" + "text": "20 22 22" }, { "type": "UncategorizedText", @@ -2259,16 +2269,6 @@ }, "text": "Sources: Bloomberg Finance L.P.; Haver Analytics; national data sources; and IMF staff calculations. Note: AEs = advanced economies; EMs = emerging markets. GFSR = Global Financial Stability Report." }, - { - "type": "UncategorizedText", - "element_id": "be54412821e5c5c1d8dd726e2a1518f1", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 11 - }, - "text": "Slowing aggregate demand and weaker-than-expected inflation prints in some major advanced economies have prompted investors’ anticipation of a further reduction in the pace of future policy rate hikes. Corporate earnings forecasts have been cut due to headwinds from slowing demand, and margins have contracted across most regions. In addition, survey-based probabilities of recession have been increasing, particularly in the United States and Europe. However, upside risks to the inflation outlook remain. Despite the recent moderation in headline inflation, core inflation remains stubbornly high across most regions, labor markets are still tight, energy prices remain pressured by Russia’s ongoing war in Ukraine, and supply chain disruptions may reappear. To keep these risks in check, financial conditions will likely need to tighten further. 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United States" }, { "type": "UncategorizedText", @@ -2331,103 +2331,103 @@ }, { "type": "UncategorizedText", - "element_id": "de5fef2c6bd3b387d19639dbc8784016", + "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "1. United States" + "text": "5" }, { "type": "UncategorizedText", - "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", + "element_id": "7de1555df0c2700329e815b93b32c571", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "5" + "text": "4" }, { "type": "UncategorizedText", - "element_id": "7de1555df0c2700329e815b93b32c571", + "element_id": "1121cfccd5913f0a63fec40a6ffd44ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "4" + "text": "3" }, { "type": "UncategorizedText", - "element_id": "7de1555df0c2700329e815b93b32c571", + "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "4" + "text": "2" }, { "type": "UncategorizedText", - "element_id": "1121cfccd5913f0a63fec40a6ffd44ea", + "element_id": "4355a46b19d348dc2f57c046f8ef63d4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "3" + "text": "1" }, { "type": "UncategorizedText", - "element_id": "1121cfccd5913f0a63fec40a6ffd44ea", + "element_id": "b1b074f02d43a5ace5633ff6df86e7c8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "3" + "text": "Oct. 22" }, { "type": "UncategorizedText", - "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", + "element_id": "fbd1fa1628fb372ebbbdd0cd0b6a2319", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "2" + "text": "Apr. 23" }, { "type": "UncategorizedText", - "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", + "element_id": "7b7dee8a185c9d1212af8b334518d5e1", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "2" + "text": "Oct. 23" }, { "type": "UncategorizedText", - "element_id": "4355a46b19d348dc2f57c046f8ef63d4", + "element_id": "d3c564f9dc1a801c1f91d8490a72b2cf", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "1" + "text": "Dec. 24" }, { "type": "UncategorizedText", - "element_id": "4355a46b19d348dc2f57c046f8ef63d4", + "element_id": "c69708757c0b20d59b95ce78d00f4fec", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "1" + "text": "Dec. 26" }, { "type": "UncategorizedText", @@ -2481,53 +2481,53 @@ }, { "type": "UncategorizedText", - "element_id": "b1b074f02d43a5ace5633ff6df86e7c8", + "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Oct. 22" + "text": "5" }, { "type": "UncategorizedText", - "element_id": "fbd1fa1628fb372ebbbdd0cd0b6a2319", + "element_id": "7de1555df0c2700329e815b93b32c571", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - "text": "Apr. 23" + "text": "4" }, { "type": "UncategorizedText", - "element_id": "7b7dee8a185c9d1212af8b334518d5e1", + "element_id": "1121cfccd5913f0a63fec40a6ffd44ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 11 }, - 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"text": " Hydro" + "text": "60" }, { "type": "UncategorizedText", - "element_id": "95cf32708a31caa478a0e9141103ac56", + "element_id": "f3869bfc418f6b38b211f34af7bbbee9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "60" + "text": " Hydro" }, { "type": "UncategorizedText", @@ -1391,23 +1391,23 @@ }, { "type": "UncategorizedText", - "element_id": "7ea9844ae84eccbf55e8330640865e36", + "element_id": "d14506655223461adf0b7bb605d29ca9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "50" + "text": "%" }, { "type": "UncategorizedText", - "element_id": "d14506655223461adf0b7bb605d29ca9", + "element_id": "7ea9844ae84eccbf55e8330640865e36", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 8 }, - "text": "%" + "text": "50" }, { "type": "UncategorizedText", @@ -1521,23 +1521,23 @@ }, { "type": "UncategorizedText", - "element_id": "ef45d070844e892dd7274e2b58d343ea", + "element_id": "792376c209f338959be4cf00c54dbf82", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Non-hydro" + "text": "500" }, { "type": "UncategorizedText", - "element_id": "792376c209f338959be4cf00c54dbf82", + "element_id": "ef45d070844e892dd7274e2b58d343ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "500" + "text": " Non-hydro" }, { "type": "UncategorizedText", @@ -1551,53 +1551,53 @@ }, { "type": "UncategorizedText", - "element_id": "b1dad634c86b14162ce382a54d48adc4", + "element_id": "e4df891c484d7abb985dadf539fa1883", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Nuclear" + "text": "400" }, { "type": "UncategorizedText", - "element_id": "e4df891c484d7abb985dadf539fa1883", + "element_id": "b1dad634c86b14162ce382a54d48adc4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "400" + "text": " Nuclear" }, { "type": "UncategorizedText", - "element_id": "a9841ec903dc8bcd39950abd149df9dd", + "element_id": "62f86400f0347bdbe07e40c3063fd3bb", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Natural gas" + "text": "h W T" }, { "type": "UncategorizedText", - "element_id": "62f86400f0347bdbe07e40c3063fd3bb", + "element_id": "f807fe6dc767be2e7021d41540114b33", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "h W T" + "text": "300" }, { "type": "UncategorizedText", - "element_id": "f807fe6dc767be2e7021d41540114b33", + "element_id": "a9841ec903dc8bcd39950abd149df9dd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "300" + "text": " Natural gas" }, { "type": "UncategorizedText", @@ -1611,23 +1611,23 @@ }, { "type": "UncategorizedText", - "element_id": "79615d00dc2ebc2416ace53ae6e85050", + "element_id": "c11e3f4837efde2441e23a7b9da02131", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": " Oil" + "text": "200" }, { "type": "UncategorizedText", - "element_id": "c11e3f4837efde2441e23a7b9da02131", + "element_id": "79615d00dc2ebc2416ace53ae6e85050", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 9 }, - "text": "200" + "text": " Oil" }, { "type": "UncategorizedText", @@ -1799,16 +1799,6 @@ }, "text": "i" }, - { - "type": "UncategorizedText", - "element_id": "228e41abf4891bbc647d29d33bed30dd", - "metadata": { - "data_source": {}, - "filetype": "application/pdf", - "page_number": 10 - }, - "text": "International Energy Agency (2018), World Energy Outlook 2018. Data accessed from https://www.iea.org/weo/ – Based on the New Policies Scenario, which incorporates existing energy policies as well as an assessment of the results likely to stem from the implementation of announced policy intentions – with visual modification by World Nuclear Association. International Energy Agency (n.d.), Statistics. Accessed from: https://www.iea.org/statistics/?country=WORLD&year=2016&category=Electricity&indicator=ElecGenByFuel&mode =chart&dataTable=ELECTRICITYANDHEAT – with visual modifications by World Nuclear Association. International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ Intergovernmental Panel on Climate Change (2018), Special Report on Global Warming of 1.5 °C. Accessed from: https://www.ipcc.ch/sr15/ International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ International Energy Agency & OECD Nuclear Energy Agency (2015), Projected Costs of generating Electricity – 2015 Edition. Accessed from: https://www.oecd-nea.org/ndd/pubs/2015/7057-proj-costs-electricity-2015.pdf International Atomic Energy Agency (2015), Technical challenges in the application and licensing of digital instrumentation and control systems in nuclear power plants. Accessed from: https://www-pub.iaea.org/MTCD/ Publications/PDF/P1695_web.pdf" - }, { "type": "UncategorizedText", "element_id": "3835a774ed6bc25ea5d9285964eafab5", @@ -1871,23 +1861,23 @@ }, { "type": "UncategorizedText", - "element_id": "825846e93b6b75f507306036dda41b1f", + "element_id": "228e41abf4891bbc647d29d33bed30dd", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "viii Paul-Scherrer Institute. Data for nuclear accidents modified to reflect UNSCEAR findings/recommendations (2012)" + "text": "International Energy Agency (2018), World Energy Outlook 2018. Data accessed from https://www.iea.org/weo/ – Based on the New Policies Scenario, which incorporates existing energy policies as well as an assessment of the results likely to stem from the implementation of announced policy intentions – with visual modification by World Nuclear Association. International Energy Agency (n.d.), Statistics. Accessed from: https://www.iea.org/statistics/?country=WORLD&year=2016&category=Electricity&indicator=ElecGenByFuel&mode =chart&dataTable=ELECTRICITYANDHEAT – with visual modifications by World Nuclear Association. International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ Intergovernmental Panel on Climate Change (2018), Special Report on Global Warming of 1.5 °C. Accessed from: https://www.ipcc.ch/sr15/ International Energy Agency (2019), Nuclear Power in a Clean Energy System. Accessed from: https://www.iea.org/ publications/nuclear/ International Energy Agency & OECD Nuclear Energy Agency (2015), Projected Costs of generating Electricity – 2015 Edition. Accessed from: https://www.oecd-nea.org/ndd/pubs/2015/7057-proj-costs-electricity-2015.pdf International Atomic Energy Agency (2015), Technical challenges in the application and licensing of digital instrumentation and control systems in nuclear power plants. Accessed from: https://www-pub.iaea.org/MTCD/ Publications/PDF/P1695_web.pdf" }, { "type": "UncategorizedText", - "element_id": "2539fec681f2aadd21c4bfceb0763445", + "element_id": "825846e93b6b75f507306036dda41b1f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 10 }, - "text": "and NRC SOARCA study 2015 International Energy Agency (2018), Electricity Information 2018 https://webstore.iea.org/electricity-information-2018-overview Ibid." + "text": "viii Paul-Scherrer Institute. Data for nuclear accidents modified to reflect UNSCEAR findings/recommendations (2012)" }, { "type": "UncategorizedText", @@ -1909,6 +1899,16 @@ }, "text": "x" }, + { + "type": "UncategorizedText", + "element_id": "2539fec681f2aadd21c4bfceb0763445", + "metadata": { + "data_source": {}, + "filetype": "application/pdf", + "page_number": 10 + }, + "text": "and NRC SOARCA study 2015 International Energy Agency (2018), Electricity Information 2018 https://webstore.iea.org/electricity-information-2018-overview Ibid." + }, { "type": "NarrativeText", "element_id": "ab9c4428d3394fd230d7636bea5030d5", @@ -1931,23 +1931,23 @@ }, { "type": "UncategorizedText", - "element_id": "821daa4396c0087d9d5ee9240bc5c85c", + "element_id": "c48603fd38d3449d3afcd2dc18903083", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" + "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" }, { "type": "UncategorizedText", - "element_id": "c48603fd38d3449d3afcd2dc18903083", + "element_id": "821daa4396c0087d9d5ee9240bc5c85c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" + "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" }, { "type": "UncategorizedText", diff --git a/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/recalibrating-risk-report.pdf.json b/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/recalibrating-risk-report.pdf.json index 0d3a1bc19b..166ef001d4 100644 --- a/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/recalibrating-risk-report.pdf.json +++ b/test_unstructured_ingest/expected-structured-output/s3/small-pdf-set/recalibrating-risk-report.pdf.json @@ -151,63 +151,63 @@ }, { "type": "UncategorizedText", - "element_id": "e61e853dddb79bd1b290a42c8bfa2c43", + "element_id": "f4ccd05b3271c386ee55d9876c745001", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Experts" + "text": "30" }, { "type": "UncategorizedText", - "element_id": "4355a46b19d348dc2f57c046f8ef63d4", + "element_id": "f14b4987904bcb5814e4459a057ed4d2", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "1" + "text": "22" }, { "type": "UncategorizedText", - "element_id": "c27f9f502d68bddce24f18d230fddc23", + "element_id": "54183f4323f377b737433a1e98229ead", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Nuclear power" + "text": "17" }, { "type": "UncategorizedText", - "element_id": "5378796307535df3ec8d8b15a2e2dc56", + "element_id": "fe6688066e4058f4d28c3956c1545589", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "20" + "text": "" }, { "type": "UncategorizedText", - "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", + "element_id": "fe6688066e4058f4d28c3956c1545589", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "2" + "text": "" }, { "type": "UncategorizedText", - "element_id": "ec8471bf2a3848a2b19b49d54c316f21", + "element_id": "fe6688066e4058f4d28c3956c1545589", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Motor vehicles" + "text": "" }, { "type": "UncategorizedText", @@ -221,23 +221,23 @@ }, { "type": "UncategorizedText", - "element_id": "1121cfccd5913f0a63fec40a6ffd44ea", + "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "3" + "text": "2" }, { "type": "UncategorizedText", - "element_id": "85d8899695f08e1eb36c352ad90fd171", + "element_id": "1121cfccd5913f0a63fec40a6ffd44ea", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Handguns" + "text": "3" }, { "type": "UncategorizedText", @@ -251,183 +251,183 @@ }, { "type": "UncategorizedText", - "element_id": "7de1555df0c2700329e815b93b32c571", + "element_id": "a3be0dc10137e55fa5239085c3f800bc", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "4" + "text": "X-rays" }, { "type": "UncategorizedText", - "element_id": "8afd0b048a86acf7393f96db0574c8ff", + "element_id": "17e163c12e373356715be3ef6e240ae9", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Smoking" + "text": "Electric power (non-nuclear)" }, { "type": "UncategorizedText", - "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", + "element_id": "8afd0b048a86acf7393f96db0574c8ff", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "2" + "text": "Smoking" }, { "type": "UncategorizedText", - "element_id": "fe6688066e4058f4d28c3956c1545589", + "element_id": "85d8899695f08e1eb36c352ad90fd171", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "Handguns" }, { "type": "UncategorizedText", - "element_id": "4deedd21c16662f9a68c10e5f0dc0c3b", + "element_id": "ec8471bf2a3848a2b19b49d54c316f21", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "Motor vehicles" }, { "type": "UncategorizedText", - "element_id": "54183f4323f377b737433a1e98229ead", + "element_id": "c27f9f502d68bddce24f18d230fddc23", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "17" + "text": "Nuclear power" }, { "type": "UncategorizedText", - "element_id": "17e163c12e373356715be3ef6e240ae9", + "element_id": "86c586f8129cc34e163eedd76b538fe8", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Electric power (non-nuclear)" + "text": "Vaccinations" }, { "type": "UncategorizedText", - "element_id": "2e6d31a5983a91251bfae5aefa1c0a19", + "element_id": "e61e853dddb79bd1b290a42c8bfa2c43", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "9" + "text": "Experts" }, { "type": "UncategorizedText", - "element_id": "fe6688066e4058f4d28c3956c1545589", + "element_id": "5378796307535df3ec8d8b15a2e2dc56", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "20" }, { "type": "UncategorizedText", - "element_id": "fe6688066e4058f4d28c3956c1545589", + "element_id": "64aeb9975f234becd55bb4635e6e2f2d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "25" }, { "type": "UncategorizedText", - "element_id": "f14b4987904bcb5814e4459a057ed4d2", + "element_id": "4deedd21c16662f9a68c10e5f0dc0c3b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "22" + "text": "" }, { "type": "UncategorizedText", - "element_id": "a3be0dc10137e55fa5239085c3f800bc", + "element_id": "fe6688066e4058f4d28c3956c1545589", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "X-rays" + "text": "" }, { "type": "UncategorizedText", - "element_id": "10159baf262b43a92d95db59dae1f72c", + "element_id": "fe6688066e4058f4d28c3956c1545589", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "7" + "text": "" }, { "type": "UncategorizedText", - "element_id": "fe6688066e4058f4d28c3956c1545589", + "element_id": "53c234e5e8472b6ac51c1ae1cab3fe06", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "2" }, { "type": "UncategorizedText", - "element_id": "fe6688066e4058f4d28c3956c1545589", + "element_id": "7de1555df0c2700329e815b93b32c571", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "" + "text": "4" }, { "type": "UncategorizedText", - "element_id": "f4ccd05b3271c386ee55d9876c745001", + "element_id": "2e6d31a5983a91251bfae5aefa1c0a19", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "30" + "text": "9" }, { "type": "UncategorizedText", - "element_id": "86c586f8129cc34e163eedd76b538fe8", + "element_id": "4355a46b19d348dc2f57c046f8ef63d4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "Vaccinations" + "text": "1" }, { "type": "UncategorizedText", - "element_id": "64aeb9975f234becd55bb4635e6e2f2d", + "element_id": "10159baf262b43a92d95db59dae1f72c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 4 }, - "text": "25" + "text": "7" }, { "type": "NarrativeText", @@ -551,23 +551,23 @@ }, { "type": "UncategorizedText", - "element_id": "75112d758c2551d782aaad167b590b1b", + "element_id": "64aeb9975f234becd55bb4635e6e2f2d", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "24.6" + "text": "25" }, { "type": "UncategorizedText", - "element_id": "64aeb9975f234becd55bb4635e6e2f2d", + "element_id": "75112d758c2551d782aaad167b590b1b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "25" + "text": "24.6" }, { "type": "UncategorizedText", @@ -601,23 +601,23 @@ }, { "type": "UncategorizedText", - "element_id": "238903180cc104ec2c5d8b3f20c5bc61", + "element_id": "a2bbdb2de53523b8099b37013f251546", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "15" + "text": "e" }, { "type": "UncategorizedText", - "element_id": "a2bbdb2de53523b8099b37013f251546", + "element_id": "238903180cc104ec2c5d8b3f20c5bc61", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "e" + "text": "15" }, { "type": "UncategorizedText", @@ -641,43 +641,43 @@ }, { "type": "UncategorizedText", - "element_id": "917df3320d778ddbaa5c5c7742bc4046", + "element_id": "fb67f6e44a2659caaa0e28f08280eb3c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "10" + "text": "a t a F" }, { "type": "UncategorizedText", - "element_id": "8048d1e7e392843de42064d4c1ae5988", + "element_id": "917df3320d778ddbaa5c5c7742bc4046", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "4.6" + "text": "10" }, { "type": "UncategorizedText", - "element_id": "fb67f6e44a2659caaa0e28f08280eb3c", + "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "a t a F" + "text": "5" }, { "type": "UncategorizedText", - "element_id": "f0b5c2c2211c8d67ed15e75e656c7862", + "element_id": "8048d1e7e392843de42064d4c1ae5988", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "5" + "text": "4.6" }, { "type": "UncategorizedText", @@ -691,123 +691,123 @@ }, { "type": "UncategorizedText", - "element_id": "7bf1f073715e4adc8472523b0d32043f", + "element_id": "9a271f2a916b0b6ee6cecb2426f0b320", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0.07" + "text": "0" }, { "type": "UncategorizedText", - "element_id": "95d020e1024da4b79092a4cd784eb0e7", + "element_id": "98ba3127e4028e41ec82ece31d2227ff", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0.04" + "text": "C oal" }, { "type": "UncategorizedText", - "element_id": "ad1d34e4d341cc6a4c4afadc494bd5c4", + "element_id": "4de0cf52492346845f7e8abfe590f19a", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0.02" + "text": "Oil" }, { "type": "UncategorizedText", - "element_id": "a37f9fe7bd3fa9d73c6b5c339b56943e", + "element_id": "041eb1afb509b6bffae0b4a339c8db5b", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0.01" + "text": "Bio m ass" }, { "type": "UncategorizedText", - "element_id": "9a271f2a916b0b6ee6cecb2426f0b320", + "element_id": "e942714ca8bde7c2efa0a45180d3bcb0", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "0" + "text": "N atural gas" }, { "type": "UncategorizedText", - "element_id": "98ba3127e4028e41ec82ece31d2227ff", + "element_id": "7bf1f073715e4adc8472523b0d32043f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "C oal" + "text": "0.07" }, { "type": "UncategorizedText", - "element_id": "4de0cf52492346845f7e8abfe590f19a", + "element_id": "0b82a6e25bae21d27740d11df2dafd18", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "Oil" + "text": "Wind" }, { "type": "UncategorizedText", - "element_id": "041eb1afb509b6bffae0b4a339c8db5b", + "element_id": "95d020e1024da4b79092a4cd784eb0e7", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "Bio m ass" + "text": "0.04" }, { "type": "UncategorizedText", - "element_id": "e942714ca8bde7c2efa0a45180d3bcb0", + "element_id": "27b098893be52637349fd0db88f6b228", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "N atural gas" + "text": "H ydropo w er" }, { "type": "UncategorizedText", - "element_id": "0b82a6e25bae21d27740d11df2dafd18", + "element_id": "ad1d34e4d341cc6a4c4afadc494bd5c4", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "Wind" + "text": "0.02" }, { "type": "UncategorizedText", - "element_id": "27b098893be52637349fd0db88f6b228", + "element_id": "e18e4f1d640d6017d6db720d7e6b2d6f", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "H ydropo w er" + "text": "S olar" }, { "type": "UncategorizedText", - "element_id": "e18e4f1d640d6017d6db720d7e6b2d6f", + "element_id": "a37f9fe7bd3fa9d73c6b5c339b56943e", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 5 }, - "text": "S olar" + "text": "0.01" }, { "type": "UncategorizedText", @@ -981,33 +981,33 @@ }, { "type": "UncategorizedText", - "element_id": "c679f20b20827cc120836b9b22b53492", + "element_id": "f5076aa15e05d1b399fcee15da62ea07", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Social and environmental costs of emissions, land-use, climate change, security of supply, etc." + "text": "Plant-level production costs at market prices" }, { "type": "UncategorizedText", - "element_id": "f5076aa15e05d1b399fcee15da62ea07", + "element_id": "32fb688e940b2045a6f54aa0b245e552", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Plant-level production costs at market prices" + "text": "Grid-level costs of the electricity system" }, { "type": "UncategorizedText", - "element_id": "32fb688e940b2045a6f54aa0b245e552", + "element_id": "c679f20b20827cc120836b9b22b53492", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 7 }, - "text": "Grid-level costs of the electricity system" + "text": "Social and environmental costs of emissions, land-use, climate change, security of supply, etc." }, { "type": "NarrativeText", @@ -1411,23 +1411,23 @@ }, { "type": "UncategorizedText", - "element_id": "821daa4396c0087d9d5ee9240bc5c85c", + "element_id": "c48603fd38d3449d3afcd2dc18903083", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" + "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" }, { "type": "UncategorizedText", - "element_id": "c48603fd38d3449d3afcd2dc18903083", + "element_id": "821daa4396c0087d9d5ee9240bc5c85c", "metadata": { "data_source": {}, "filetype": "application/pdf", "page_number": 12 }, - "text": "World Nuclear Association Tower House 10 Southampton Street London WC2E 7HA United Kingdom" + "text": "+44 (0)20 7451 1520 www.world-nuclear.org info@world-nuclear.org" }, { "type": "UncategorizedText", diff --git a/unstructured/file_utils/filetype.py b/unstructured/file_utils/filetype.py index d031b7027e..f4e267ae56 100644 --- a/unstructured/file_utils/filetype.py +++ b/unstructured/file_utils/filetype.py @@ -7,22 +7,16 @@ import zipfile from enum import Enum from functools import wraps -from typing import IO, TYPE_CHECKING, Callable, List, Optional +from typing import IO, Callable, Optional -from unstructured.documents.coordinates import PixelSpace -from unstructured.documents.elements import Element, PageBreak from unstructured.file_utils.encoding import detect_file_encoding, format_encoding_str from unstructured.nlp.patterns import LIST_OF_DICTS_PATTERN from unstructured.partition.common import ( _add_element_metadata, _remove_element_metadata, exactly_one, - normalize_layout_element, ) -if TYPE_CHECKING: - from unstructured_inference.inference.layout import DocumentLayout, PageLayout - try: import magic @@ -501,105 +495,6 @@ def _check_eml_from_buffer(file: IO) -> bool: return EMAIL_HEAD_RE.match(file_head) is not None -def document_to_element_list( - document: "DocumentLayout", - include_page_breaks: bool = False, - sort: bool = False, - last_modification_date: Optional[str] = None, - **kwargs, -) -> List[Element]: - """Converts a DocumentLayout object to a list of unstructured elements.""" - elements: List[Element] = [] - num_pages = len(document.pages) - for i, page in enumerate(document.pages): - page_elements: List[Element] = [] - - page_image_metadata = _get_page_image_metadata(page) - image_format = page_image_metadata.get("format") - image_width = page_image_metadata.get("width") - image_height = page_image_metadata.get("height") - - for layout_element in page.elements: - if image_width and image_height and hasattr(layout_element, "coordinates"): - coordinate_system = PixelSpace(width=image_width, height=image_height) - else: - coordinate_system = None - - element = normalize_layout_element(layout_element, coordinate_system=coordinate_system) - - if isinstance(element, List): - for el in element: - if last_modification_date: - el.metadata.last_modified = last_modification_date - el.metadata.page_number = i + 1 - page_elements.extend(element) - continue - else: - if last_modification_date: - element.metadata.last_modified = last_modification_date - element.metadata.text_as_html = ( - layout_element.text_as_html if hasattr(layout_element, "text_as_html") else None - ) - page_elements.append(element) - coordinates = ( - element.metadata.coordinates.points if element.metadata.coordinates else None - ) - _add_element_metadata( - element, - page_number=i + 1, - filetype=image_format, - coordinates=coordinates, - coordinate_system=coordinate_system, - **kwargs, - ) - if sort: - page_elements = sorted( - page_elements, - key=lambda el: ( - el.metadata.coordinates.points[0][1] - if el.metadata.coordinates - else float("inf"), - el.metadata.coordinates.points[0][0] - if el.metadata.coordinates - else float("inf"), - el.id, - ), - ) - if include_page_breaks and i < num_pages - 1: - page_elements.append(PageBreak(text="")) - elements.extend(page_elements) - - return elements - - -def _get_page_image_metadata( - page: PageLayout, -) -> dict: - """Retrieve image metadata and coordinate system from a page.""" - - image = getattr(page, "image", None) - image_metadata = getattr(page, "image_metadata", None) - - if image: - image_format = image.format - image_width = image.width - image_height = image.height - elif image_metadata: - image_format = image_metadata.get("format") - image_width = image_metadata.get("width") - image_height = image_metadata.get("height") - else: - image_format = None - image_width = None - image_height = None - - return { - "format": image_format, - "width": image_width, - "height": image_height, - } - - PROGRAMMING_LANGUAGES = [ "javascript", "python", diff --git a/unstructured/partition/common.py b/unstructured/partition/common.py index 8975aa48f4..a0ba32ed85 100644 --- a/unstructured/partition/common.py +++ b/unstructured/partition/common.py @@ -10,7 +10,7 @@ import emoji from tabulate import tabulate -from unstructured.documents.coordinates import CoordinateSystem +from unstructured.documents.coordinates import CoordinateSystem, PixelSpace from unstructured.documents.elements import ( TYPE_TO_TEXT_ELEMENT_MAP, CheckBox, @@ -23,12 +23,17 @@ ) from unstructured.logger import logger from unstructured.nlp.patterns import ENUMERATED_BULLETS_RE, UNICODE_BULLETS_RE +from unstructured.partition.utils.constants import SORT_MODE_XY_CUT from unstructured.utils import dependency_exists if dependency_exists("docx") and dependency_exists("docx.table"): from docx.table import Table as docxtable +if dependency_exists("numpy") and dependency_exists("cv2"): + from unstructured.partition.utils.sorting import sort_page_elements + if TYPE_CHECKING: + from unstructured_inference.inference.layout import DocumentLayout, PageLayout from unstructured_inference.inference.layoutelement import ( LayoutElement, LocationlessLayoutElement, @@ -365,3 +370,95 @@ def contains_emoji(s: str) -> bool: """ return bool(emoji.emoji_count(s)) + + +def _get_page_image_metadata( + page: PageLayout, +) -> dict: + """Retrieve image metadata and coordinate system from a page.""" + + image = getattr(page, "image", None) + image_metadata = getattr(page, "image_metadata", None) + + if image: + image_format = image.format + image_width = image.width + image_height = image.height + elif image_metadata: + image_format = image_metadata.get("format") + image_width = image_metadata.get("width") + image_height = image_metadata.get("height") + else: + image_format = None + image_width = None + image_height = None + + return { + "format": image_format, + "width": image_width, + "height": image_height, + } + + +def document_to_element_list( + document: "DocumentLayout", + sortable: bool = False, + include_page_breaks: bool = False, + last_modification_date: Optional[str] = None, + **kwargs, +) -> List[Element]: + """Converts a DocumentLayout object to a list of unstructured elements.""" + elements: List[Element] = [] + sort_mode = kwargs.get("sort_mode", SORT_MODE_XY_CUT) + num_pages = len(document.pages) + for i, page in enumerate(document.pages): + page_elements: List[Element] = [] + + page_image_metadata = _get_page_image_metadata(page) + image_format = page_image_metadata.get("format") + image_width = page_image_metadata.get("width") + image_height = page_image_metadata.get("height") + + for layout_element in page.elements: + if image_width and image_height and hasattr(layout_element, "coordinates"): + coordinate_system = PixelSpace(width=image_width, height=image_height) + else: + coordinate_system = None + + element = normalize_layout_element(layout_element, coordinate_system=coordinate_system) + + if isinstance(element, List): + for el in element: + if last_modification_date: + el.metadata.last_modified = last_modification_date + el.metadata.page_number = i + 1 + page_elements.extend(element) + continue + else: + if last_modification_date: + element.metadata.last_modified = last_modification_date + element.metadata.text_as_html = ( + layout_element.text_as_html if hasattr(layout_element, "text_as_html") else None + ) + page_elements.append(element) + coordinates = ( + element.metadata.coordinates.points if element.metadata.coordinates else None + ) + _add_element_metadata( + element, + page_number=i + 1, + filetype=image_format, + coordinates=coordinates, + coordinate_system=coordinate_system, + **kwargs, + ) + + sorted_page_elements = page_elements + if sortable and sort_mode == SORT_MODE_XY_CUT: + sorted_page_elements = sort_page_elements(page_elements, sort_mode) + + if include_page_breaks and i < num_pages - 1: + sorted_page_elements.append(PageBreak(text="")) + elements.extend(sorted_page_elements) + + return elements diff --git a/unstructured/partition/html.py b/unstructured/partition/html.py index 8996529b3b..9b9ddde937 100644 --- a/unstructured/partition/html.py +++ b/unstructured/partition/html.py @@ -10,9 +10,9 @@ from unstructured.file_utils.filetype import ( FileType, add_metadata_with_filetype, - document_to_element_list, ) from unstructured.partition.common import ( + document_to_element_list, exactly_one, get_last_modified_date, get_last_modified_date_from_file, @@ -121,6 +121,7 @@ def partition_html( return document_to_element_list( document, + sortable=False, include_page_breaks=include_page_breaks, last_modification_date=metadata_last_modified or last_modification_date, **kwargs, diff --git a/unstructured/partition/pdf.py b/unstructured/partition/pdf.py index 588ca11078..a4667c9c3d 100644 --- a/unstructured/partition/pdf.py +++ b/unstructured/partition/pdf.py @@ -24,11 +24,11 @@ from unstructured.file_utils.filetype import ( FileType, add_metadata_with_filetype, - document_to_element_list, ) from unstructured.nlp.patterns import PARAGRAPH_PATTERN from unstructured.partition.common import ( convert_to_bytes, + document_to_element_list, exactly_one, get_last_modified_date, get_last_modified_date_from_file, @@ -36,6 +36,8 @@ ) from unstructured.partition.strategies import determine_pdf_or_image_strategy from unstructured.partition.text import element_from_text, partition_text +from unstructured.partition.utils.constants import SORT_MODE_BASIC, SORT_MODE_XY_CUT +from unstructured.partition.utils.sorting import sort_page_elements from unstructured.utils import requires_dependencies RE_MULTISPACE_INCLUDING_NEWLINES = re.compile(pattern=r"\s+", flags=re.DOTALL) @@ -111,12 +113,14 @@ def extractable_elements( file: Optional[Union[bytes, BinaryIO, SpooledTemporaryFile]] = None, include_page_breaks: bool = False, metadata_last_modified: Optional[str] = None, + **kwargs, ): return _partition_pdf_with_pdfminer( filename=filename, file=file, include_page_breaks=include_page_breaks, metadata_last_modified=metadata_last_modified, + **kwargs, ) @@ -172,6 +176,7 @@ def partition_pdf_or_image( file=spooled_to_bytes_io_if_needed(file), include_page_breaks=include_page_breaks, metadata_last_modified=metadata_last_modified or last_modification_date, + **kwargs, ) pdf_text_extractable = any( isinstance(el, Text) and el.text.strip() for el in extracted_elements @@ -270,9 +275,10 @@ def _partition_pdf_or_image_local( ) elements = document_to_element_list( layout, + sortable=True, include_page_breaks=include_page_breaks, - sort=False, last_modification_date=metadata_last_modified, + **kwargs, ) out_elements = [] @@ -302,6 +308,7 @@ def _partition_pdf_with_pdfminer( file: Optional[BinaryIO] = None, include_page_breaks: bool = False, metadata_last_modified: Optional[str] = None, + **kwargs, ) -> List[Element]: """Partitions a PDF using PDFMiner instead of using a layoutmodel. Used for faster processing or detectron2 is not available. @@ -320,6 +327,7 @@ def _partition_pdf_with_pdfminer( filename=filename, include_page_breaks=include_page_breaks, metadata_last_modified=metadata_last_modified, + **kwargs, ) elif file: @@ -329,6 +337,7 @@ def _partition_pdf_with_pdfminer( filename=filename, include_page_breaks=include_page_breaks, metadata_last_modified=metadata_last_modified, + **kwargs, ) return elements @@ -358,9 +367,11 @@ def _process_pdfminer_pages( filename: str = "", include_page_breaks: bool = False, metadata_last_modified: Optional[str] = None, + **kwargs, ): """Uses PDF miner to split a document into pages and process them.""" elements: List[Element] = [] + sort_mode = kwargs.get("sort_mode", SORT_MODE_XY_CUT) for i, page in enumerate(extract_pages(fp)): # type: ignore width, height = page.width, page.height @@ -404,14 +415,9 @@ def _process_pdfminer_pages( ) page_elements.append(element) - sorted_page_elements = sorted( - page_elements, - key=lambda el: ( - el.metadata.coordinates.points[0][1] if el.metadata.coordinates else float("inf"), - el.metadata.coordinates.points[0][0] if el.metadata.coordinates else float("inf"), - el.id, - ), - ) + sorted_page_elements = sort_page_elements(page_elements, SORT_MODE_BASIC) + if sort_mode != SORT_MODE_BASIC: + sorted_page_elements = sort_page_elements(sorted_page_elements, sort_mode) elements += sorted_page_elements if include_page_breaks: diff --git a/unstructured/partition/utils/__init__.py b/unstructured/partition/utils/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/unstructured/partition/utils/constants.py b/unstructured/partition/utils/constants.py new file mode 100644 index 0000000000..5095345f24 --- /dev/null +++ b/unstructured/partition/utils/constants.py @@ -0,0 +1,2 @@ +SORT_MODE_XY_CUT = "xy-cut" +SORT_MODE_BASIC = "basic" diff --git a/unstructured/partition/utils/sorting.py b/unstructured/partition/utils/sorting.py new file mode 100644 index 0000000000..79293fe5f2 --- /dev/null +++ b/unstructured/partition/utils/sorting.py @@ -0,0 +1,60 @@ +from typing import List + +import numpy as np + +from unstructured.documents.elements import CoordinatesMetadata, Element +from unstructured.partition.utils.constants import SORT_MODE_BASIC, SORT_MODE_XY_CUT +from unstructured.partition.utils.xycut import recursive_xy_cut + + +def coordinates_to_bbox(coordinates: CoordinatesMetadata) -> List[int]: + points = coordinates.points + left, top = points[0] + right, bottom = points[2] + return [int(left), int(top), int(right), int(bottom)] + + +def sort_page_elements( + page_elements: List[Element], + sort_mode: str = SORT_MODE_XY_CUT, +) -> List[Element]: + """ + Sorts a list of page elements based on the specified sorting mode. + + Parameters: + - page_elements (List[Element]): A list of elements representing parts of a page. Each element + should have metadata containing coordinates. + - sort_mode (str, optional): The mode by which the elements will be sorted. Default is + SORT_MODE_XY_CUT. + - SORT_MODE_XY_CUT: Sorts elements based on XY-cut sorting approach. Requires the + recursive_xy_cut function and coordinates_to_bbox function to be defined. + - SORT_MODE_BASIC: Sorts elements based on their coordinates. Elements without coordinates + will be pushed to the end. + - If an unrecognized sort_mode is provided, the function returns the elements as-is. + + Returns: + - List[Element]: A list of sorted page elements. + """ + + if not page_elements: + return [] + + if sort_mode == SORT_MODE_XY_CUT: + coordinates_list = [el.metadata.coordinates for el in page_elements] + boxes = [coordinates_to_bbox(coords) for coords in coordinates_list] + res: List[int] = [] + recursive_xy_cut(np.asarray(boxes).astype(int), np.arange(len(boxes)), res) + sorted_page_elements = [page_elements[i] for i in res] + elif sort_mode == SORT_MODE_BASIC: + sorted_page_elements = sorted( + page_elements, + key=lambda el: ( + el.metadata.coordinates.points[0][1] if el.metadata.coordinates else float("inf"), + el.metadata.coordinates.points[0][0] if el.metadata.coordinates else float("inf"), + el.id, + ), + ) + else: + sorted_page_elements = page_elements + + return sorted_page_elements diff --git a/unstructured/partition/utils/xycut.py b/unstructured/partition/utils/xycut.py new file mode 100644 index 0000000000..c95ab2dc6b --- /dev/null +++ b/unstructured/partition/utils/xycut.py @@ -0,0 +1,255 @@ +from typing import List + +import cv2 +import numpy as np + +""" + +This module contains the implementation of the XY-Cut sorting approach +from: https://github.com/Sanster/xy-cut + +""" + + +def projection_by_bboxes(boxes: np.ndarray, axis: int) -> np.ndarray: + """ + 通过一组 bbox 获得投影直方图，最后以 per-pixel 形式输出 + + Args: + boxes: [N, 4] + axis: 0-x坐标向水平方向投影， 1-y坐标向垂直方向投影 + + Returns: + 1D 投影直方图，长度为投影方向坐标的最大值(我们不需要图片的实际边长，因为只是要找文本框的间隔) + + """ + assert axis in [0, 1] + length = np.max(boxes[:, axis::2]) + res = np.zeros(length, dtype=int) + # TODO: how to remove for loop? + for start, end in boxes[:, axis::2]: + res[start:end] += 1 + return res + + +# from: https://dothinking.github.io/2021-06-19-%E9%80%92%E5%BD%92%E6%8A%95%E5%BD%B1 +# %E5%88%86%E5%89%B2%E7%AE%97%E6%B3%95/#:~:text=%E9%80%92%E5%BD%92%E6%8A%95%E5%BD%B1 +# %E5%88%86%E5%89%B2%EF%BC%88Recursive%20XY,%EF%BC%8C%E5%8F%AF%E4%BB%A5%E5%88%92 +# %E5%88%86%E6%AE%B5%E8%90%BD%E3%80%81%E8%A1%8C%E3%80%82 +def split_projection_profile(arr_values: np.ndarray, min_value: float, min_gap: float): + """Split projection profile: + + ``` + ┌──┐ + arr_values │ │ ┌─┐─── + ┌──┐ │ │ │ │ | + │ │ │ │ ┌───┐ │ │min_value + │ │<- min_gap ->│ │ │ │ │ │ | + ────┴──┴─────────────┴──┴─┴───┴─┴─┴─┴─── + 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 + ``` + + Args: + arr_values (np.array): 1-d array representing the projection profile. + min_value (float): Ignore the profile if `arr_value` is less than `min_value`. + min_gap (float): Ignore the gap if less than this value. + + Returns: + tuple: Start indexes and end indexes of split groups. + """ + # all indexes with projection height exceeding the threshold + arr_index = np.where(arr_values > min_value)[0] + if not len(arr_index): + return + + # find zero intervals between adjacent projections + # | | || + # ||||<- zero-interval -> ||||| + arr_diff = arr_index[1:] - arr_index[0:-1] + arr_diff_index = np.where(arr_diff > min_gap)[0] + arr_zero_intvl_start = arr_index[arr_diff_index] + arr_zero_intvl_end = arr_index[arr_diff_index + 1] + + # convert to index of projection range: + # the start index of zero interval is the end index of projection + arr_start = np.insert(arr_zero_intvl_end, 0, arr_index[0]) + arr_end = np.append(arr_zero_intvl_start, arr_index[-1]) + arr_end += 1 # end index will be excluded as index slice + + return arr_start, arr_end + + +def recursive_xy_cut(boxes: np.ndarray, indices: np.ndarray, res: List[int]): + """ + + Args: + boxes: (N, 4) + indices: 递归过程中始终表示 box 在原始数据中的索引 + res: 保存输出结果 + + """ + # 向 y 轴投影 + assert len(boxes) == len(indices) + + _indices = boxes[:, 1].argsort() + y_sorted_boxes = boxes[_indices] + y_sorted_indices = indices[_indices] + + # debug_vis(y_sorted_boxes, y_sorted_indices) + + y_projection = projection_by_bboxes(boxes=y_sorted_boxes, axis=1) + pos_y = split_projection_profile(y_projection, 0, 1) + if not pos_y: + return + + arr_y0, arr_y1 = pos_y + for r0, r1 in zip(arr_y0, arr_y1): + # [r0, r1] 表示按照水平切分，有 bbox 的区域，对这些区域会再进行垂直切分 + _indices = (r0 <= y_sorted_boxes[:, 1]) & (y_sorted_boxes[:, 1] < r1) + + y_sorted_boxes_chunk = y_sorted_boxes[_indices] + y_sorted_indices_chunk = y_sorted_indices[_indices] + + _indices = y_sorted_boxes_chunk[:, 0].argsort() + x_sorted_boxes_chunk = y_sorted_boxes_chunk[_indices] + x_sorted_indices_chunk = y_sorted_indices_chunk[_indices] + + # 往 x 方向投影 + x_projection = projection_by_bboxes(boxes=x_sorted_boxes_chunk, axis=0) + pos_x = split_projection_profile(x_projection, 0, 1) + if not pos_x: + continue + + arr_x0, arr_x1 = pos_x + if len(arr_x0) == 1: + # x 方向无法切分 + res.extend(x_sorted_indices_chunk) + continue + + # x 方向上能分开，继续递归调用 + for c0, c1 in zip(arr_x0, arr_x1): + _indices = (c0 <= x_sorted_boxes_chunk[:, 0]) & (x_sorted_boxes_chunk[:, 0] < c1) + recursive_xy_cut( + x_sorted_boxes_chunk[_indices], + x_sorted_indices_chunk[_indices], + res, + ) + + +def points_to_bbox(points): + assert len(points) == 8 + + # [x1,y1,x2,y2,x3,y3,x4,y4] + left = min(points[::2]) + right = max(points[::2]) + top = min(points[1::2]) + bottom = max(points[1::2]) + + left = max(left, 0) + top = max(top, 0) + right = max(right, 0) + bottom = max(bottom, 0) + return [left, top, right, bottom] + + +def bbox2points(bbox): + left, top, right, bottom = bbox + return [left, top, right, top, right, bottom, left, bottom] + + +def vis_polygon(img, points, thickness=2, color=None): + br2bl_color = color + tl2tr_color = color + tr2br_color = color + bl2tl_color = color + cv2.line( + img, + (points[0][0], points[0][1]), + (points[1][0], points[1][1]), + color=tl2tr_color, + thickness=thickness, + ) + + cv2.line( + img, + (points[1][0], points[1][1]), + (points[2][0], points[2][1]), + color=tr2br_color, + thickness=thickness, + ) + + cv2.line( + img, + (points[2][0], points[2][1]), + (points[3][0], points[3][1]), + color=br2bl_color, + thickness=thickness, + ) + + cv2.line( + img, + (points[3][0], points[3][1]), + (points[0][0], points[0][1]), + color=bl2tl_color, + thickness=thickness, + ) + return img + + +def vis_points( + img: np.ndarray, + points, + texts: List[str], + color=(0, 200, 0), +) -> np.ndarray: + """ + + Args: + img: + points: [N, 8] 8: x1,y1,x2,y2,x3,y3,x3,y4 + texts: + color: + + Returns: + + """ + points = np.array(points) + assert len(texts) == points.shape[0] + + for i, _points in enumerate(points): + vis_polygon(img, _points.reshape(-1, 2), thickness=2, color=color) + bbox = points_to_bbox(_points) + left, top, right, bottom = bbox + cx = (left + right) // 2 + cy = (top + bottom) // 2 + + txt = texts[i] + font = cv2.FONT_HERSHEY_SIMPLEX + cat_size = cv2.getTextSize(txt, font, 0.5, 2)[0] + + img = cv2.rectangle( + img, + (cx - 5 * len(txt), cy - cat_size[1] - 5), + (cx - 5 * len(txt) + cat_size[0], cy - 5), + color, + -1, + ) + + img = cv2.putText( + img, + txt, + (cx - 5 * len(txt), cy - 5), + font, + 0.5, + (255, 255, 255), + thickness=1, + lineType=cv2.LINE_AA, + ) + + return img + + +def vis_polygons_with_index(image, points): + texts = [str(i) for i in range(len(points))] + res_img = vis_points(image.copy(), points, texts) + return res_img