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Relation Extraction

Datasets

Sentence-Level Datasets

  1. ACE 2005 Dataset. [link] [paper]
  2. SemEval-2010 Task 8 Dataset. [link] [paper]
  3. TACRED. [link] [paper]

Document-Level Datasets

  1. SciREX. ACL 2020. [link] [paper]
  2. DocRED. ACL 2019. [link] [paper]
  3. GDA. RECOM 2019. [link] [paper] [preprocess]
  4. SciERC. EMNLP 2018. [link] [paper]
  5. CDR. Database 2016. [link1] [link2] [paper] [preprocess]

Distantly Supervised Datasets

  1. NYT Dataset. [link] [paper]

Few-shot Datasets

  1. FewRel. [link] [1.0 paper] [2.0 paper]

Survey papers

  1. Relation Extraction Using Distant Supervision: A Survey. ALISA SMIRNOVA and PHILIPPE CUDRÉ-MAUROUX. ACM Computing Surveys 2018.

  2. A Survey of Deep Learning Methods for Relation Extraction. Shantanu Kumar. Arxiv Preprint 2017.

  3. Relation Extraction : A Survey. Sachin Pawara,b, Girish K. Palshikara, Pushpak Bhattacharyyab. Arxiv Preprint 2017.

  4. A Review of Relation Extraction. Nguyen Bach, Sameer Badaskar. 2017.

  5. More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction. Xu Han, Tianyu Gao, Yankai Lin, Hao Peng, Yaoliang Yang, Chaojun Xiao, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. Arxiv Preprint 2020.

  6. Neural relation extraction: a survey. Mehmet Aydar, Ozge Bozal, Furkan Ozbay. Arxiv Preprint 2020.

Journal and Conference Papers

Sentence-Level RE Methods

  1. Beyond Word Attention: Using Segment Attention in Neural Relation Extraction. Bowen Yu, Zhenyu Zhang, Tingwen Liu, Bin Wang, Sujian Li, Quangang Li. IJCAI 2019. [paper] [code] [note] [file]

  2. Matching the Blanks Distributional Similarity for Relation Learning. Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, Tom Kwiatkowski. ACL 2019. [paper] [code] [note] [file]

  3. Attention Guided Graph Convolutional Networks for Relation Extraction. Yan Zhang, Zhijiang Guo, Wei Lu. ACL 2019. [paper] [code] [note] [file]

  4. Relation Extraction as Two-way Span-Prediction. Amir DN Cohen, Shachar Rosenman, Yoav Goldberg. arxiv 2020. [paper] [code] [note] [file]

Document-level RE Methods

  1. Global-to-Local Neural Networks for Document-Level Relation Extraction. Difeng Wang, Wei Hu, Ermei Cao, Weijian Sun. EMNLP 2020. [paper] [code] [note] [file]

  2. Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling. Wenxuan Zhou, Kevin Huang, Tengyu Ma, Jing Huang. ArXiv 2020. [paper] [code] [note] [file]

Joint Extraction of Entities and Relations Methods

  1. CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning. Daojian Zeng, Haoran Zhang, Qianying Liu. AAAI 2020. [paper] [code] [note] [file]

  2. A Novel Hierarchical Binary Tagging Framework for Joint Extraction of Entities and Relations. Zhepei Wei, Jianlin Su, Yue Wang, Yuan Tian, Yi Chang. AAAI 2020. [paper] [code] [note] [file]

  3. GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction. Tsu-Jui Fu, Peng-Hsuan Li, Wei-Yun Ma. ACL 2019. [paper] [code] [note] [file]

  4. Span-Level Model for Relation Extraction. Kalpit Dixit, Yaser Al-Onaizan. ACL 2019. [paper] [code] [note] [file]

  5. Span-based Joint Entity and Relation Extraction with Transformer Pre-training. Markus Eberts and Adrian Ulges. arxiv 2019. [paper] [code] [note] [file]

  6. Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction. Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng,Fei Cheng, Daisuke Kawahara and Sadao Kurohashi EMNLP 2020.(finding) [paper] [code] [note] [file]

  7. Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations. Kai Sun, Richong Zhang, Samuel Mensah, Yongyi Mao, Xudong Liu EMNLP2020. [paper] [file]

  8. Two are Better than One:Joint Entity and Relation Extraction with Table-Sequence Encoders. Jue Wang and Wei Lu EMNLP2020. [paper] [code] [note] [file]

Distant Supervised Methods

  1. Relation Extraction with Temporal Reasoning Based on Memory Augmented Distant Supervision. Jianhao Yan, Lin He, Ruqin Huang, Jian Li, Ying Liu. NAACL 2019. [paper] [code] [note] [file]

  2. Effective Deep Memory Networks for Distant Supervised Relation Extraction. Xiaocheng Feng, Jiang Guo, Bing Qin, Ting Liu, Yongjie Liu SCIR. IJCAI 2017. [paper] [code] [note] [file]

  3. Self-Attention Enhanced CNNs and Collaborative Curriculum Learning for Distantly Supervised Relation Extraction. Yuyun Huang Jinhua Du. EMNLP 2019. [paper] [code] [note] [file]

  4. Graph Neural Networks with Generated Parameters for Relation Extraction. Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-seng Chua, Maosong Sun. ACL 2019. [paper] [code] [note] [file]

  5. Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction. Qinyuan Ye, Liyuan Liu, Maosen Zhang, Xiang Ren. EMNLP 2019. [paper] [code] [note] [file]

Few Shot RE methods

  1. FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation Han, X., Zhu, H., Yu, P., Wang, Z., Yao, Y., Liu, Z., & Sun, M. EMNLP2018 [paper] [code] [note] [file]