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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 61–70 of 445 papers

Title	Date	Tasks	Status	Hype
Bidirectional Recurrent Convolutional Neural Network for Relation Classification	Aug 1, 2016	ClassificationGeneral Classification	—Unverified	0
Bidirectional Long Short-Term Memory Networks for Relation Classification	Oct 1, 2015	ClassificationGeneral Classification	—Unverified	0
A non-DNN Feature Engineering Approach to Dependency Parsing -- FBAML at CoNLL 2017 Shared Task	Aug 1, 2017	Dependency ParsingFeature Engineering	—Unverified	0
Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification	Aug 30, 2018	16kDiscourse Parsing	—Unverified	0
Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach for Relation Classification	Mar 5, 2024	Few-Shot Relation ClassificationRelation	—Unverified	0
A Bi-LSTM-RNN Model for Relation Classification Using Low-Cost Sequence Features	Aug 27, 2016	Dependency ParsingGeneral Classification	—Unverified	0
Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths	Sep 1, 2015	Question AnsweringRelation Classification	—Unverified	0
A VSM-based Statistical Model for the Semantic Relation Interpretation of Noun-Modifier Pairs	Sep 1, 2015	Question AnsweringRelation	—Unverified	0
AutoRC: Improving BERT Based Relation Classification Models via Architecture Search	Sep 22, 2020	General ClassificationNeural Architecture Search	—Unverified	0
A Dependency-Based Neural Network for Relation Classification	Jul 16, 2015	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	MTB Baldini Soares et al. (2019)	F1	71.5	—	Unverified
6	KnowBERT	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