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 81–90 of 106 papers

TitleStatusHype
Document-level Relation Extraction as Semantic SegmentationCode1
Discriminative Reasoning for Document-level Relation ExtractionCode1
Three Sentences Are All You Need: Local Path Enhanced Document Relation ExtractionCode1
SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation ExtractionCode1
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
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation ExtractionCode1
An End-to-end Model for Entity-level Relation Extraction using Multi-instance LearningCode1
Document-Level Relation Extraction with ReconstructionCode1
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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