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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 271–280 of 445 papers

Title	Date	Tasks	Status	Hype
End-to-end neural relation extraction using deep biaffine attention	Dec 29, 2018	General ClassificationRelation	CodeCode Available	0
Customized Attention Mechanism for Relation Classification	Dec 1, 2018	ClassificationRelation	—Unverified	0
Improving Scientific Relation Classification with Task Specific Supersense	Dec 1, 2018	ClassificationRelation	—Unverified	0
Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification	Nov 5, 2018	ClassificationDiscourse Parsing	—Unverified	0
Argumentative Link Prediction using Residual Networks and Multi-Objective Learning	Nov 1, 2018	Argument MiningComponent Classification	CodeCode Available	1
Zero-shot Relation Classification as Textual Entailment	Nov 1, 2018	ClassificationGeneral Classification	—Unverified	0
Frame- and Entity-Based Knowledge for Common-Sense Argumentative Reasoning	Nov 1, 2018	Argument MiningCommon Sense Reasoning	CodeCode Available	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
Revisiting neural relation classification in clinical notes with external information	Oct 1, 2018	ClassificationFeature Engineering	CodeCode Available	0
Logician and Orator: Learning from the Duality between Language and Knowledge in Open Domain	Oct 1, 2018	Open Information Extractionreinforcement-learning	—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