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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 181–190 of 445 papers

Title	Date	Tasks	Status	Hype
Few-Shot Text Classification with Edge-Labeling Graph Neural Network-Based Prototypical Network	Dec 1, 2020	Few-Shot Text ClassificationGraph Neural Network	—Unverified	0
Combining Lexical and Spatial Knowledge to Predict Spatial Relations between Objects in Images	Aug 1, 2016	Object DetectionObject Recognition	—Unverified	0
Combining Recurrent and Convolutional Neural Networks for Relation Classification	May 24, 2016	ClassificationGeneral Classification	—Unverified	0
A Stacking Gated Neural Architecture for Implicit Discourse Relation Classification	Nov 1, 2016	Feature EngineeringGeneral Classification	—Unverified	0
End-to-End Models for Chemical-Protein Interaction Extraction: Better Tokenization and Span-Based Pipeline Strategies	Apr 3, 2023	Chemical-Protein Interaction Extractionnamed-entity-recognition	—Unverified	0
From Learning-to-Match to Learning-to-Discriminate:Global Prototype Learning for Few-shot Relation Classification	Aug 1, 2021	ClassificationFew-Shot Relation Classification	—Unverified	0
Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters	Mar 29, 2019	RelationRelation Classification	—Unverified	0
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification	Apr 26, 2022	Few-Shot LearningMeta-Learning	—Unverified	0
Embracing Non-Traditional Linguistic Resources for Low-resource Language Name Tagging	Nov 1, 2017	Relation ClassificationWord Embeddings	—Unverified	0
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings	Jun 1, 2018	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