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 51–60 of 106 papers

TitleStatusHype
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple ExtractionCode0
Extracting Polymer Nanocomposite Samples from Full-Length DocumentsCode0
FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation ExtractionCode0
Fine-tune Bert for DocRED with Two-step ProcessCode0
Global Context-enhanced Graph Convolutional Networks for Document-level Relation ExtractionCode0
HistRED: A Historical Document-Level Relation Extraction DatasetCode0
Improving Document-level Relation Extraction via Contextualizing Mention Representations and Weighting Mention PairsCode0
LLM with Relation Classifier for Document-Level Relation ExtractionCode0
Multi-view Inference for Relation Extraction with Uncertain KnowledgeCode0
On the Robustness of Document-Level Relation Extraction Models to Entity Name VariationsCode0
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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