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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 251–260 of 445 papers

Title	Date	Tasks	Status	Hype	Score
Talla at SemEval-2018 Task 7: Hybrid Loss Optimization for Relation Classification using Convolutional Neural Networks	Jun 1, 2018	Feature EngineeringGeneral Classification	—Unverified	0	0
Task-Oriented Learning of Word Embeddings for Semantic Relation Classification	Feb 28, 2015	ClassificationGeneral Classification	—Unverified	0	0
TDDiscourse: A Dataset for Discourse-Level Temporal Ordering of Events	Sep 1, 2019	ArticlesRelation Classification	—Unverified	0	0
TDRE: A Tensor Decomposition Based Approach for Relation Extraction	Oct 15, 2020	RelationRelation Classification	—Unverified	0	0
Temporal Event Knowledge Acquisition via Identifying Narratives	May 28, 2018	General ClassificationRelation Classification	—Unverified	0	0
Temporal Relation Classification Based on Temporal Reasoning	Mar 1, 2013	ClassificationGeneral Classification	—Unverified	0	0
Temporal Relation Classification in Persian and English contexts	Sep 1, 2013	ClassificationGeneral Classification	—Unverified	0	0
Temporal Relation Classification using a Model of Tense and Aspect	Sep 1, 2015	General ClassificationRelation	—Unverified	0	0
Texterra at SemEval-2018 Task 7: Exploiting Syntactic Information for Relation Extraction and Classification in Scientific Papers	Jun 1, 2018	ClassificationGeneral Classification	—Unverified	0	0
The DCU Discourse Parser for Connective, Argument Identification and Explicit Sense Classification	Jul 1, 2015	General ClassificationRelation 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