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Relation Classification

Relation Classification is the task of identifying the semantic relation holding between two nominal entities in text.

Source: Structure Regularized Neural Network for Entity Relation Classification for Chinese Literature Text

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 201–210 of 445 papers

Title	Date	Tasks	Status	Hype
Investigation of BERT Model on Biomedical Relation Extraction Based on Revised Fine-tuning Mechanism	Nov 1, 2020	RelationRelation Classification	—Unverified	0
Logic-guided Semantic Representation Learning for Zero-Shot Relation Classification	Oct 30, 2020	ClassificationDescriptive	—Unverified	0
RH-Net: Improving Neural Relation Extraction via Reinforcement Learning and Hierarchical Relational Searching	Oct 27, 2020	Denoisingreinforcement-learning	CodeCode Available	0
Meta-Learning for Neural Relation Classification with Distant Supervision	Oct 26, 2020	ClassificationGeneral Classification	—Unverified	0
Learning to Decouple Relations: Few-Shot Relation Classification with Entity-Guided Attention and Confusion-Aware Training	Oct 21, 2020	Few-Shot Relation ClassificationRelation	—Unverified	0
TDRE: A Tensor Decomposition Based Approach for Relation Extraction	Oct 15, 2020	RelationRelation Classification	—Unverified	0
Relation Classification as Two-way Span-Prediction	Oct 9, 2020	ClassificationGeneral Classification	—Unverified	0
小样本关系分类研究综述(Few-Shot Relation Classification: A Survey)	Oct 1, 2020	Few-Shot Relation ClassificationRelation Classification	—Unverified	0
Entity Relative Position Representation based Multi-head Selection for Joint Entity and Relation Extraction	Oct 1, 2020	Joint Entity and Relation ExtractionLanguage Modeling	—Unverified	0
AutoRC: Improving BERT Based Relation Classification Models via Architecture Search	Sep 22, 2020	General ClassificationNeural Architecture Search	—Unverified	0

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All datasets TACRED SemEval-2010 Task-8 FewRel AbstRCT - Neoplasm CDCP Discovery DRI Corpus MATRES

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeepEx (zero-shot top-10)	F1	76.4	—	Unverified
2	DeepStruct multi-task	F1	74.9	—	Unverified
3	LUKE 483M	F1	72.7	—	Unverified
4	K-Adapter	F1	72	—	Unverified
5	KnowBERT	F1	71.5	—	Unverified
6	MTB Baldini Soares et al. (2019)	F1	71.5	—	Unverified
7	RoBERTa	F1	71.3	—	Unverified
8	SpanBERT	F1	70.8	—	Unverified
9	ERNIE	F1	68	—	Unverified
10	ERNIE	F1	67.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BRCNN	F1	86.3	—	Unverified
2	DRNNs	F1	86.1	—	Unverified
3	depLCNN + NS	F1	85.6	—	Unverified
4	SDP-LSTM	F1	83.7	—	Unverified
5	DepNN	F1	83.6	—	Unverified
6	MVRNN	F1	82.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepStruct multi-task w/ finetune	F1 (10-way 1-shot)	97.8	—	Unverified
2	DeepEx (zero-shot top-10)	F1	92.9	—	Unverified
3	DeepStruct multi-task	F1 (10-way 1-shot)	92.2	—	Unverified
4	Deepstruct zero-shot	F1 (10-way 1-shot)	67.6	—	Unverified
5	DeepEx (zero-shot top-1)	F1	48.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResAttArg	Macro F1	70.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResAttArg	Macro F1	42.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT	1:1 Accuracy	20.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResAttArg	Macro F1	37.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SCS-EERE	F1	0.83	—	Unverified