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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 141–150 of 445 papers

Title	Date	Tasks	Status	Hype
About Evaluation of F1 Score for RECENT Relation Extraction System	May 16, 2023	RelationRelation Classification	—Unverified	0
Classifying medical relations in clinical text via convolutional neural networks	May 17, 2018	ClassificationGeneral Classification	—Unverified	0
Enhanced Protein-Protein Interactions Extraction from the Literature using Entity Type- and Position-aware Representation	Jan 16, 2022	PositionRelation	—Unverified	0
Classifying Lexical-semantic Relationships by Exploiting Sense/Concept Representations	Apr 1, 2017	General ClassificationMulti-class Classification	—Unverified	0
ARNOR: Attention Regularization based Noise Reduction for Distant Supervision Relation Classification	Jul 1, 2019	ClassificationGeneral Classification	—Unverified	0
EoANN: Lexical Semantic Relation Classification Using an Ensemble of Artificial Neural Networks	Sep 1, 2019	General ClassificationKnowledge Graphs	—Unverified	0
Argument Relation Classification Using a Joint Inference Model	Sep 1, 2017	Argument MiningClassification	—Unverified	0
Classification de relations pour l'intelligence \'economique et concurrentielle (Relation Classification for Competitive and Economic Intelligence )	Jun 1, 2020	ClassificationGeneral Classification	—Unverified	0
Enhancing Contextual Word Representations Using Embedding of Neighboring Entities in Knowledge Graphs	Oct 1, 2022	Entity TypingKnowledge Graphs	—Unverified	0
Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives	May 1, 2020	General ClassificationImplicit Discourse Relation Classification	—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