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 11–20 of 106 papers

TitleStatusHype
Document-Level Relation Extraction with Adaptive Thresholding and Localized Context PoolingCode1
A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of LabelingCode1
DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation ExtractionCode1
Anaphor Assisted Document-Level Relation ExtractionCode1
DocRED: A Large-Scale Document-Level Relation Extraction DatasetCode1
Denoising Relation Extraction from Document-level Distant SupervisionCode1
An End-to-end Model for Entity-level Relation Extraction using Multi-instance LearningCode1
Discriminative Reasoning for Document-level Relation ExtractionCode1
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and GenesCode1
Enhancing Biomedical Relation Extraction with DirectionalityCode1
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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