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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 221–230 of 445 papers

Title	Date	Tasks	Status	Hype
Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations	May 1, 2020	General ClassificationMulti-Task Learning	—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
MICK: A Meta-Learning Framework for Few-shot Relation Classification with Small Training Data	Apr 26, 2020	ClassificationFew-Shot Learning	—Unverified	0
Improving Scholarly Knowledge Representation: Evaluating BERT-based Models for Scientific Relation Classification	Apr 13, 2020	ClassificationGeneral Classification	—Unverified	0
Unsupervised Adversarial Domain Adaptation for Implicit Discourse Relation Classification	Mar 4, 2020	ClassificationDomain Adaptation	—Unverified	0
KEML: A Knowledge-Enriched Meta-Learning Framework for Lexical Relation Classification	Feb 25, 2020	General ClassificationMeta-Learning	—Unverified	0
A Neural Approach to Discourse Relation Signal Detection	Jan 8, 2020	RelationRelation Classification	—Unverified	0
Learning to Relate from Captions and Bounding Boxes	Dec 1, 2019	Image CaptioningRelation Classification	—Unverified	0
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction	Nov 27, 2019	Entity EmbeddingsRelation	—Unverified	0
Improving Relation Classification by Entity Pair Graph	Nov 17, 2019	ClassificationGeneral 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