wiki-all-6-3-tamber-bm25.template

# Anserini Regressions: QA on Wikipedia Sliding Windows

**Models**: BM25

This page documents QA regression experiments on the `wiki-all-6-3-tamber` corpus, which is integrated into Anserini's regression testing framework.
The exact configuration here is the 6/3 sentence sliding window corpus described in the following paper:

> Manveer Singh Tamber, Ronak Pradeep, and Jimmy Lin. [Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.](https://link.springer.com/chapter/10.1007/978-3-031-28241-6_11) _Proceedings of the 45th European Conference on Information Retrieval (ECIR 2023), Part III_, pages 163–176, April 2023, Dublin, Ireland.

The exact configurations for these regressions are stored in [this YAML file](${yaml}).
Note that this page is automatically generated from [this template](${template}) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.

From one of our Waterloo servers (e.g., `orca`), the following command will perform the complete regression, end to end:

```bash
python src/main/python/run_regression.py --index --verify --search --regression ${test_name}
```

## Indexing

Typical indexing command:

```bash
${index_cmds}
```

The directory `/path/to/${corpus}/`should be a directory containing the wiki-all-6-3-tamber passages collection retrieved from [here](https://huggingface.co/datasets/castorini/odqa-wiki-corpora).

For additional details, see explanation of [common indexing options](${root_path}/docs/common-indexing-options.md).

## Retrieval

Topics and qrels are stored [here](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels), which is linked to the Anserini repo as a submodule.
The regression experiments here evaluate on the test sets of Natural Questions, TriviaQA, SQuAD, and WebQuestions.

After indexing has completed, you should be able to perform retrieval as follows:

```bash
${ranking_cmds}
```

The trec format will need to be converted to DPR's JSON format for evaluation:
```bash
${converting_cmds}
```

Evaluation can be performed using scripts from pyserini:

```bash
${eval_cmds}
```

## Effectiveness

With the above commands, you should be able to reproduce the following results:

${effectiveness}

## Reproduction Log[*](${root_path}/docs/reproducibility.md)

To add to this reproduction log, modify [this template](${template}) and run `bin/build.sh` to rebuild the documentation.