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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 301–310 of 445 papers

Title	Date	Tasks	Status	Hype
Improving Scientific Relation Classification with Task Specific Supersense	Dec 1, 2018	ClassificationRelation	—Unverified	0
Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives	May 1, 2015	Discourse ParsingNatural Language Understanding	—Unverified	0
Improving Vision-and-Language Reasoning via Spatial Relations Modeling	Nov 9, 2023	Position regressionRelation	—Unverified	0
Improving Zero-shot Relation Classification via Automatically-acquired Entailment Templates	Jul 13, 2023	Natural Language InferenceRelation	—Unverified	0
Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning	Oct 13, 2021	Contrastive LearningFew-Shot Learning	—Unverified	0
Inducing Latent Semantic Relations for Structured Distributional Semantics	Aug 1, 2014	Information RetrievalQuestion Answering	—Unverified	0
Inter-Weighted Alignment Network for Sentence Pair Modeling	Sep 1, 2017	Machine TranslationNatural Language Inference	—Unverified	0
Investigation of annotator's behaviour using eye-tracking data	Aug 1, 2013	ChunkingCoreference Resolution	—Unverified	0
Investigation of BERT Model on Biomedical Relation Extraction Based on Revised Fine-tuning Mechanism	Nov 1, 2020	RelationRelation Classification	—Unverified	0
IRCMS at SemEval-2018 Task 7 : Evaluating a basic CNN Method and Traditional Pipeline Method for Relation Classification	Jun 1, 2018	General ClassificationNamed Entity Recognition (NER)	—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