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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 321–330 of 445 papers

Title	Date	Tasks	Status	Hype
GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification	Apr 15, 2018	ClassificationGeneral Classification	CodeCode Available	0
ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction	Apr 5, 2018	General ClassificationRelation Classification	—Unverified	0
Structure Regularized Neural Network for Entity Relation Classification for Chinese Literature Text	Mar 15, 2018	General ClassificationRelation	—Unverified	0
Tag-Enhanced Tree-Structured Neural Networks for Implicit Discourse Relation Classification	Mar 3, 2018	General ClassificationImplicit Discourse Relation Classification	—Unverified	0
OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers using Piecewise Convolutional Neural Networks	Feb 25, 2018	ClassificationData Augmentation	—Unverified	0
SEE: Syntax-aware Entity Embedding for Neural Relation Extraction	Jan 11, 2018	RelationRelation Classification	—Unverified	0
False Positive and Cross-relation Signals in Distant Supervision Data	Nov 14, 2017	General ClassificationRelation	CodeCode Available	0
Structure Regularized Bidirectional Recurrent Convolutional Neural Network for Relation Classification	Nov 6, 2017	ClassificationGeneral Classification	—Unverified	0
Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification	Nov 1, 2017	General ClassificationImplicit Discourse Relation Classification	—Unverified	0
Learning Transferable Representation for Bilingual Relation Extraction via Convolutional Neural Networks	Nov 1, 2017	Knowledge Base PopulationQuestion Answering	—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