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IE Dataset Zoo

Information extraction dataset zoo.

Relation Extraction

Dataset #Rel. #Inst. Feature Source Resource Origin
Fewrel 100 44,800 Supervised Wikipedia+Wikidata url url
TACRED 42 68,120 Supervised Newswire+web - url
Semeval 19 8,000 Supervised Web url url
Wikidata 352 495,883 Distent-supervision Wikipedia+Wikidata url url
NYT10(tsinghua) 53 522,043 Distent-supervision NYT+Freebase url url
NYT10-large(tsinghua) 53 570,088 Distent-supervision NYT+Freebase url url
NYT-Wikidata 100 882,177 Distent-supervision NYT+Wikidata url url
NYT10-29 29 70,339 Distent-supervision NYT+Freebase url url
NYT11-12 12 62,648 DS+supervised NYT+Freebase url url
NYT-manual 24 235,982 Distent-supervision NYT+Freebase url url
NYT-Wiki(zju) 73 1,989,377 Distent-supervision NYT-Wikipedia-Wikidata url url
Wiki-KBP 19 23,784 Distent-supervision Wikipedia+KBP+Freebase url url
PubMed-BioInfer 94 1,580 Distent-supervision PubMed+NESH - url
WebNLG 14 75,325 Supervised Web - url
SKE 50 173,108 Supervised Web url url
KBP37 37 15,916 Supervised Web url url
T-REx 642 6.3M Distent-supervision Wikipedia+Wikidata - url
Google-RE 5 59,576 Supervised Wikipedia - url
ADE 3 23,516 Supervised Medical Report url url

Other Datasets

Fewrel

FewRel : A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation

Matching the Blanks : Distributional Similarity for Relation Learning ACL2019

Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification ACL2019

TACRED

Position-aware attention and supervised data improve slot filling.

Matching the Blanks : Distributional Similarity for Relation Learning ACL2019

Semeval

Matching the Blanks : Distributional Similarity for Relation Learning

Wikidata

Context-Aware Representations for Knowledge Base Relation Extraction

Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction

NYT10(tsinghua)

Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks

Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction

NYT10-large (tsinghua)

Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction EMNLP2018

Hierarchical Relation Extraction with Coarse-to-Fine Grained Attention EMNLP2018

Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks NAACL2019

NYT-Wikidata

Incorporating Relation Paths in Neural Relation Extraction EMNLP2017

NYT10-29

A Hierarchical Framework for Relation Extraction with Reinforcement Learning

Joint Extraction of Entities and Relations with a Hierarchical Multi-task Tagging Model

NYT11-12

A Hierarchical Framework for Relation Extraction with Reinforcement Learning

Joint Extraction of Entities and Relations with a Hierarchical Multi-task Tagging Model

NYT-manual

Indirect Supervision for Relation Extraction Using Question-Answer Pairs

CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases.

Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy

Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism

Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme

NYT-Wiki(zju)

Relation Adversarial Network for Low Resource Knowledge Graph Completion

Wiki-KBP

CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases.

Indirect Supervision for Relation Extraction Using Question-Answer Pairs

PubMed-BioInfer

CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases.

WebNLG

Extracting relational facts by an end-to-end neural model with copy mechanism

SKE

MrMep: joint extraction of multiple relations and multiple entity pairs based on triplet attention

KBP37

Matching the Blanks : Distributional Similarity for Relation Learning ACL2019

Relation classification via recurrent neural network

T-REx

T-Rex : A Large Scale Alignment of Natural Language with Knowledge Base Triples

K-ADAPTER: Infusing Knowledge into Pre-Trained Models with Adapters

Event Extraction

Dataset # Inst. Feature Source Resource Origin
ACE05 599 Supervised Web - url
FewEvent(zju) 71,385 Supervised ACE05+_TAC-KBP17 url url
CCKS2019_Event 17,815 Supervised Financial Announcements url url
Doc2EDAG 32,040 Supervised Financial Announcements url url

ACE05

too many papers

FewEvent(zju)

Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection

Doc2EDAG

Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction

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