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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 351–360 of 445 papers

Title	Date	Tasks	Status	Hype
On the Need of Cross Validation for Discourse Relation Classification	Apr 1, 2017	ClassificationGeneral Classification	—Unverified	0
Neural Temporal Relation Extraction	Apr 1, 2017	PositionRelation	—Unverified	0
Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification	Apr 1, 2017	ClassificationGeneral Classification	—Unverified	0
A Joint Framework for Argumentative Text Analysis Incorporating Domain Knowledge	Jan 19, 2017	General ClassificationRelation	—Unverified	0
Pairwise Relation Classification with Mirror Instances and a Combined Convolutional Neural Network	Dec 1, 2016	ClassificationGeneral Classification	—Unverified	0
CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks	Dec 1, 2016	Machine TranslationParaphrase Generation	—Unverified	0
A Unified Architecture for Semantic Role Labeling and Relation Classification	Dec 1, 2016	ClassificationFeature Engineering	—Unverified	0
Semantic Relation Classification via Hierarchical Recurrent Neural Network with Attention	Dec 1, 2016	ClassificationGeneral Classification	—Unverified	0
CATENA: CAusal and TEmporal relation extraction from NAtural language texts	Dec 1, 2016	General ClassificationQuestion Answering	CodeCode Available	0
Attention-Based Convolutional Neural Network for Semantic Relation Extraction	Dec 1, 2016	Feature EngineeringGeneral Classification	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