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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 151–160 of 445 papers

Title	Date	Tasks	Status	Hype
Argument Pair Extraction with Mutual Guidance and Inter-sentence Relation Graph	Nov 1, 2021	Argument Pair Extraction (APE)Relation	—Unverified	0
Distilling Relation Embeddings from Pretrained Language Models	Nov 1, 2021	Knowledge GraphsLanguage Modeling	—Unverified	0
A Data Bootstrapping Recipe for Low Resource Multilingual Relation Classification	Oct 18, 2021	ClassificationRelation	—Unverified	0
Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning	Oct 13, 2021	Contrastive LearningFew-Shot Learning	—Unverified	0
On the Relation between Syntactic Divergence and Zero-Shot Performance	Oct 9, 2021	Cross-lingual zero-shot dependency parsingDependency Parsing	CodeCode Available	0
Generate Triggers in Neural Relation Extraction	Sep 29, 2021	DecoderRelation	—Unverified	0
Distilling Relation Embeddings from Pre-trained Language Models	Sep 21, 2021	Knowledge GraphsLanguage Modeling	—Unverified	0
DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection	Sep 20, 2021	ClassificationConnective Detection	CodeCode Available	0
Supervised Relation Classification as Two-way Span-Prediction	Sep 17, 2021	ClassificationPrediction	—Unverified	0
SORNet: Spatial Object-Centric Representations for Sequential Manipulation	Sep 8, 2021	ObjectRelation Classification	CodeCode Available	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