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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 231–240 of 445 papers

Title	Date	Tasks	Status	Hype	Score
Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling	Jun 25, 2015	General ClassificationRelation	—Unverified	0	0
Semantic Relation Classification via Hierarchical Recurrent Neural Network with Attention	Dec 1, 2016	ClassificationGeneral Classification	—Unverified	0	0
SemEval-2012 Task 2: Measuring Degrees of Relational Similarity	Jul 1, 2012	Relation ClassificationTask 2	—Unverified	0	0
SemEval-2013 Task 1: TempEval-3: Evaluating Time Expressions, Events, and Temporal Relations	Jun 1, 2013	Event ExtractionRelation Classification	—Unverified	0	0
SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers	Jun 1, 2018	ClassificationGeneral Classification	—Unverified	0	0
SERC: Syntactic and Semantic Sequence based Event Relation Classification	Nov 3, 2021	ClassificationNatural Language Inference	—Unverified	0	0
Shallow Discourse Parsing with Syntactic and (a Few) Semantic Features	Jul 1, 2015	Discourse ParsingRelation Classification	—Unverified	0	0
Simple Customization of Recursive Neural Networks for Semantic Relation Classification	Oct 1, 2013	ClassificationGeneral Classification	—Unverified	0	0
SIRIUS-LTG-UiO at SemEval-2018 Task 7: Convolutional Neural Networks with Shortest Dependency Paths for Semantic Relation Extraction and Classification in Scientific Papers	Apr 24, 2018	ClassificationGeneral Classification	—Unverified	0	0
Spectral Semi-Supervised Discourse Relation Classification	Jul 1, 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