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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 341–350 of 445 papers

Title	Date	Tasks	Status	Hype
Multilevel Heuristics for Rationale-Based Entity Relation Classification in Sentences	Aug 1, 2018	ClassificationGeneral Classification	—Unverified	0
Multimodal Relational Triple Extraction with Query-based Entity Object Transformer	Aug 16, 2024	Knowledge GraphsObject	—Unverified	0
Multi-Perspective Document Revision	Oct 1, 2022	Grammatical Error CorrectionRelation Classification	—Unverified	0
Multiple Range-Restricted Bidirectional Gated Recurrent Units with Attention for Relation Classification	Jul 5, 2017	ClassificationGeneral Classification	—Unverified	0
Neural Network Models for Implicit Discourse Relation Classification in English and Chinese without Surface Features	Jun 7, 2016	Discourse ParsingGeneral Classification	—Unverified	0
Neural Relation Classification with Text Descriptions	Aug 1, 2018	ClassificationGeneral Classification	—Unverified	0
Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning	May 22, 2019	Argument MiningComponent Classification	—Unverified	0
FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation	Oct 24, 2018	ClassificationFew-Shot Learning	CodeCode Available	0
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification	Oct 16, 2019	ClassificationDomain Adaptation	CodeCode Available	0
Comparative Analysis of AI Agent Architectures for Entity Relationship Classification	Jun 3, 2025	AI AgentRelation	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