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【Great】Knowledge Graphs - 2020
Article: 史上最全《知识图谱》2020综述论文,18位作者, 130页pdf
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Learning Entity and Relation Embeddings for Knowledge Graph Completion - THU2015
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COMET: Commonsense Transformers for Automatic Knowledge Graph Construction - Allen2019
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How much is a Triple? Estimating the Cost of Knowledge Graph Creation - Germany2018
Chinese: 67 亿美金搞个图,创建知识图谱的成本有多高你知道吗?
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https://github.com/liuhuanyong/KnowledgeGraphSlides
中文知识图谱计算会议CCKS报告合集,涵盖从2013年至2018年,共48篇,从中可以看出从谷歌2012年推出知识图谱以来,中国学术界及工业界这6年来知识图谱的主流思想变迁。
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Distant supervision for relation extraction without labeled data - Stanford2009
远程监督 = 监督学习 + Bootstrapping
Article: 关系抽取之远程监督算法 - 2019
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思知 智能时代:史上最大规模1.4亿中文知识图谱开源下载
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https://github.com/wuxiyu/transE (Python)
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https://github.com/liuhuanyong/CausalityEventExtraction
基于因果关系知识库的因果事件图谱实验项目,本项目罗列了因果显式表达的几种模式,基于这种模式和大规模语料,再经过融合等操作,可形成因果事件图谱。
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https://github.com/liuhuanyong/HyponymyExtraction
基于知识概念体系,百科知识库,以及在线搜索结构化方式的词语上下位抽取与可视化展示
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https://github.com/liuhuanyong/EventTriplesExtraction
基于依存句法与语义角色标注的事件三元组抽取,可用于文本理解如文档主题链,事件线等应用
瑞金医院MMC人工智能辅助构建知识图谱大赛
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https://github.com/zhpmatrix/tianchi-ruijin (Keras)
baseline, BiLSTM+CRF, 只做了第一阶段实体识别,作为NER来做,第二阶段是关系抽取,其实可以End-to-End一起做
2019百度信息抽取比赛
抽取满足约束的SPO三元组知识, http://lic2019.ccf.org.cn/kg
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https://github.com/bojone/kg-2019 (Keras)
Rank 7 基于CNN + Attenton + 自行设计的标注结构的信息抽取模型
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https://github.com/zhengyima/kg-baseline-pytorch (PyTorch)
使用Pytorch实现苏神的模型,F1在dev集可达到0.75,联合关系抽取,Joint Relation Extraction.
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https://github.com/wangpeiyi9979/IE-Bert-CNN (PyTorch)
BERT + CNN
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https://github.com/chenbjin/RepresentationLearning
知识表示相关学习算法
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https://github.com/liuhuanyong/ProductKnowledgeGraph
基于京东网站的商品上下级概念、商品品牌之间关系和商品描述维度等知识库,可以支持商品属性库构建、商品销售问答、品牌物品生产等知识查询服务,也可用于情感分析等下游应用。
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https://github.com/thunlp/JointNRE (Tensorflow)
Joint Neural Relation Extraction with Text and KGs
Paper: 1
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https://github.com/shiningliang/CCKS2019-IPRE (Tensorflow)
CCKS2019-人物关系抽取
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https://github.com/mengxiaoxu/entity_relation_extraction (Java)
基于依存分析的实体关系抽取简单实现,即抽取事实三元组
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https://github.com/lawlietAi/relation-classification-via-attention-model (PyTorch)
code of Relation Classification via Multi-Level Attention CNNs
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https://github.com/hadyelsahar/CNN-RelationExtraction (Tensorflow)
CNN for relation extraction between two given entities
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https://github.com/lemonhu/open-entity-relation-extraction
Knowledge triples extraction and knowledge base construction based on dependency syntax for open domain text.
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Article: 【清华大学-腾讯】关系提取综述
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Code: https://github.com/thunlp/Chinese_NRE (PyTorch)
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【论文】Awesome Relation Classification Paper - 2019
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【论文】Awesome Relation Extraction Paper - 2019
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https://github.com/gswycf/Joint-Extraction-of-Entities-and-Relations-Based-on-a-Novel-Tagging-Scheme (PyTorch)
Joint Extraction of Entities and Relations Based on cnn+rnn
Paper: paper1, 2
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https://github.com/zsctju/triplets-extraction (Keras)
Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
Paper: paper1
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https://github.com/WindChimeRan/pytorch_multi_head_selection_re (PyTorch)
reproduce "Joint entity recognition and relation extraction as a multi-head selection problem" for Chinese IE
Paper: paper3
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https://github.com/sanmusunrise/NPNs
Paper: paper4