/REPaperList

Must-read papers on relation extraction.

REPaperList

😆 Must-read papers on relation extraction especifically for low-resource setting.

Datasets

Dataset #train #dev #test #rel no_relation entity type
TACRED [link | paper] 68,124 22,631 15,509 42 ✔ ✔
TACREV [link | paper] 68,124 22,631 15,509 42 ✔ ✔
Re-TACRED [link | paper] 58,465 19,584 13,418 40 ✔ ✔
Wiki80 [link | paper] 50,400 5,600 -- 80 ✘ ✘
FewRel 1.0 [link | paper] 44,800 11,200 14,000* 100 (64/16/20) ✘ ✘
FewRel 2.0 [link | paper] 44,800 2,500 (64 / 25) ✘ ✘

(*--> unpublic)

Dataset #train #dev #test #rel #tuples (train | test) entity overlap type (NEO/EPO/SEO)
NYT24 [link | paper] 56,196 5,000 24 88,366 | 8,120 37,371 / 15,124 / 18,825 | 3,289 / 1,410 / 1,711
NYT29 [link | paper] 63,306 4,006 29 78,973 | 5,859 53,444 / 8,379 / 9,862 | 2,963 / 898 / 1,043
WebNLG [link | paper ] 5,019 500 703 216
ACE05 [link]
ACE04 [link]
SciERC [link | paper ] 1,861 275 551 7

Papers

Low-resource relation extraction

N-way-K-shot setups

  • FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation. [pdf], [project]

  • FewRel 2.0: Towards More Challenging Few-Shot Relation Classification. [pdf], [project]

  • Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification. [pdf], [project]

  • Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification. [pdf], [project]

  • Matching the Blanks: Distributional Similarity for Relation Learning. [pdf], [project]

  • Hierarchical Attention Prototypical Networks for Few-Shot Text Classification. [pdf ]

  • Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs. [pdf], [project]

  • Enhance Prototypical Network with Text Descriptions for Few-shot Relation Classification. [pdf]

  • Learning from Context or Names? An Empirical Study on Neural Relation Extraction. [pdf], [project]

  • Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction. [pdf]

  • Entity Concept-enhanced Few-shot Relation Extraction. [pdf], [project]

  • Learning Discriminative and Unbiased Representations for Few-Shot Relation Extraction. [pdf]]

  • Zero-shot Relation Classification from Side Information. [pdf], [project]

  • MapRE: An Effective Semantic Mapping Approach for Low-resource Relation Extraction [pdf]

  • Exploring Task Difficulty for Few-Shot Relation Extraction. [pdf], [project]

  • Towards Realistic Few-Shot Relation Extraction. [pdf], [project]

Generalized few-shot setups

  • KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction. [pdf], [project]
  • PTR: Prompt Tuning with Rules for Text Classification. [pdf], [project]
  • GradLRE: Gradient Imitation Reinforcement Learning for Low resource Relation Extraction. [pdf], [project]
  • Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction. [pdf], [project]

Triple Extraction

Joint Extraction of Entities and Relations

Sentence-level relation extraction

Transformer-based models