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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 101–110 of 445 papers

Title	Date	Tasks	Status	Hype
Cross Domain Few-Shot Learning via Meta Adversarial Training	Feb 11, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified	0
Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks	Jan 24, 2022	DenoisingQuestion Answering	CodeCode Available	1
Enhanced Protein-Protein Interactions Extraction from the Literature using Entity Type- and Position-aware Representation	Jan 16, 2022	PositionRelation	—Unverified	0
Prompt-based Zero-shot Relation Classification with Semantic Knowledge Augmentation	Jan 16, 2022	RelationRelation Classification	—Unverified	0
From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction	Jan 16, 2022	Enumerative SearchFew-Shot Learning	CodeCode Available	1
VRDFormer: End-to-End Video Visual Relation Detection With Transformers	Jan 1, 2022	ObjectRelation	—Unverified	0
Budget Sensitive Reannotation of Noisy Relation Classification Data Using Label Hierarchy	Dec 26, 2021	RelationRelation Classification	—Unverified	0
Unified Named Entity Recognition as Word-Word Relation Classification	Dec 19, 2021	Chinese Named Entity RecognitionClassification	CodeCode Available	1
Knowledge-Augmented Language Models for Cause-Effect Relation Classification	Dec 16, 2021	Cause-Effect Relation ClassificationClassification	CodeCode Available	1
CogALex 2.0: Impact of Data Quality on Lexical-Semantic Relation Prediction	Dec 14, 2021	Hypernym DiscoveryRelation	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