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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 341–350 of 445 papers

Title	Date	Tasks	Status	Hype	Score
Budget Sensitive Reannotation of Noisy Relation Classification Data Using Label Hierarchy	Dec 26, 2021	RelationRelation Classification	—Unverified	0	0
CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification	Nov 11, 2022	Classificationcounterfactual	—Unverified	0	0
Chain Based RNN for Relation Classification	May 1, 2015	ClassificationDependency Parsing	—Unverified	0	0
ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations	Apr 28, 2023	Discourse ParsingIn-Context Learning	—Unverified	0	0
Chinese Relation Classification using Long Short Term Memory Networks	May 1, 2018	ClassificationGeneral Classification	—Unverified	0	0
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings	Jun 1, 2018	ClassificationGeneral Classification	—Unverified	0	0
Classification de relations pour l'intelligence \'economique et concurrentielle (Relation Classification for Competitive and Economic Intelligence )	Jun 1, 2020	ClassificationGeneral Classification	—Unverified	0	0
Classifying Lexical-semantic Relationships by Exploiting Sense/Concept Representations	Apr 1, 2017	General ClassificationMulti-class Classification	—Unverified	0	0
Classifying medical relations in clinical text via convolutional neural networks	May 17, 2018	ClassificationGeneral Classification	—Unverified	0	0
Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Path	Aug 15, 2015	ClassificationGeneral Classification	—Unverified	0	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