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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 191–200 of 445 papers

Title	Date	Tasks	Status	Hype	Score
Global Context for improving recognition of Online Handwritten Mathematical Expressions	May 21, 2021	ClassificationRelation	—Unverified	0	0
Generative Prompt Tuning for Relation Classification	Nov 16, 2021	ClassificationLanguage Modeling	—Unverified	0	0
Comparing Convolutional Neural Networks to Traditional Models for Slot Filling	Mar 16, 2016	ClassificationGeneral Classification	—Unverified	0	0
AmalREC: A Dataset for Relation Extraction and Classification Leveraging Amalgamation of Large Language Models	Dec 29, 2024	RelationRelation Classification	—Unverified	0	0
A Data Bootstrapping Recipe for Low-Resource Multilingual Relation Classification	Nov 1, 2021	ClassificationRelation	—Unverified	0	0
Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition Extraction	Dec 1, 2020	ClassificationDefinition Extraction	—Unverified	0	0
A Constituent-Based Approach to Argument Labeling with Joint Inference in Discourse Parsing	Oct 1, 2014	Discourse ParsingRelation Classification	—Unverified	0	0
A Bi-LSTM-RNN Model for Relation Classification Using Low-Cost Sequence Features	Aug 27, 2016	Dependency ParsingGeneral Classification	—Unverified	0	0
Generate Triggers in Neural Relation Extraction	Sep 29, 2021	DecoderRelation	—Unverified	0	0
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification	Apr 26, 2022	Few-Shot LearningMeta-Learning	—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