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 71–80 of 106 papers

TitleStatusHype
Seq2rel: A sequence-to-sequence-based approach for document-level relation extraction—0
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction—0
SagDRE: Sequence-Aware Graph-Based Document-Level Relation Extraction with Adaptive Margin LossCode0
Learning Logic Rules for Document-level Relation ExtractionCode1
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation ExtractionCode1
Modular Self-Supervision for Document-Level Relation Extraction—0
Entity and Evidence Guided Document-Level Relation Extraction—0
MRN: A Locally and Globally Mention-Based Reasoning Network for Document-Level Relation ExtractionCode1
EIDER: Evidence-enhanced Document-level Relation Extraction—0
Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage FusionCode1
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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