SOTAVerified

Document-level Relation Extraction

Document-level RE aim to identify the relations of various entity pairs expressed across multiple sentences.

Papers

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Showing 91–100 of 106 papers

TitleStatusHype
Modular Self-Supervision for Document-Level Relation Extraction—0
Entity and Evidence Guided Document-Level Relation Extraction—0
EIDER: Evidence-enhanced Document-level Relation Extraction—0
Multi-view Inference for Relation Extraction with Uncertain KnowledgeCode0
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
Mention-centered Graph Neural Network for Document-level Relation Extraction—0
Coarse-to-Fine Entity Representations for Document-level Relation ExtractionCode0
Global Context-enhanced Graph Convolutional Networks for Document-level Relation ExtractionCode0
Graph Enhanced Dual Attention Network for Document-Level Relation Extraction—0
Document-level Relation Extraction with Dual-tier Heterogeneous Graph—0
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All datasetsBc8DocRED-IEDWIERe-DocRED

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BioRex+DirectionalityEvaluation Macro F156.06—Unverified
#ModelMetricClaimedVerifiedStatus
1REXELRelation F160.1—Unverified
#ModelMetricClaimedVerifiedStatus
1VaeDiff-DocREF10.73—Unverified
#ModelMetricClaimedVerifiedStatus
1VaeDiff-DocREF10.79—Unverified