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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 131–140 of 445 papers

Title	Date	Tasks	Status	Hype	Score
ERNIE: Enhanced Language Representation with Informative Entities	May 17, 2019	Entity LinkingEntity Typing	CodeCode Available	0	5
Enhancing Targeted Minority Class Prediction in Sentence-Level Relation Extraction	Jun 29, 2022	RelationRelation Classification	CodeCode Available	0	5
Enriching Pre-trained Language Model with Entity Information for Relation Classification	May 20, 2019	General ClassificationLanguage Modeling	CodeCode Available	0	5
Experiments with Three Approaches to Recognizing Lexical Entailment	Jan 31, 2014	General ClassificationLexical Entailment	CodeCode Available	0	5
Borrowing Human Senses: Comment-Aware Self-Training for Social Media Multimodal Classification	Mar 27, 2023	ClassificationHate Speech Detection	CodeCode Available	0	5
Extracting Protein-Protein Interactions (PPIs) from Biomedical Literature using Attention-based Relational Context Information	Mar 8, 2024	RelationRelation Classification	CodeCode Available	0	5
Do Models Learn the Directionality of Relations? A New Evaluation: Relation Direction Recognition	May 19, 2021	RelationRelation Classification	CodeCode Available	0	5
Distant Supervision for Relation Extraction with Matrix Completion	Jun 1, 2014	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available	0	5
End-to-end neural relation extraction using deep biaffine attention	Dec 29, 2018	General ClassificationRelation	CodeCode Available	0	5
Efficient Information Extraction in Few-Shot Relation Classification through Contrastive Representation Learning	Mar 25, 2024	ClassificationContrastive Learning	CodeCode Available	0	5

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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