Datasets › DocRED

DocRED

Introduced by Yuan Yao et al. in DocRED: A Large-Scale Document-Level Relation Extraction Dataset1 Jan 2019 archive 2025-07-28

DocRED (Document-Level Relation Extraction Dataset) is a relation extraction dataset constructed from Wikipedia and Wikidata. Each document in the dataset is human-annotated with named entity mentions, coreference information, intra- and inter-sentence relations, and supporting evidence. DocRED requires reading multiple sentences in a document to extract entities and infer their relations by synthesizing all information of the document. Along with the human-annotated data, the dataset provides large-scale distantly supervised data.

DocRED contains 132,375 entities and 56,354 relational facts annotated on 5,053 Wikipedia documents. In addition to the human-annotated data, the dataset provides large-scale distantly supervised data over 101,873 documents.

Source: DocRED: A Large-Scale Document-Level Relation Extraction Dataset Image Source: DocRED: A Large-Scale Document-Level Relation Extraction Dataset

Benchmarks archive 2025-07-28

All 4 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

Papers archive 2025-07-28

30 shown of 43 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 155. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linking 1 2 19 Apr 2024 ran 3 of 3 samples (0 unverified)
DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation Extraction 1 1 17 Feb 2023 not harvested
Enhancing Document-level Relation Extraction by Entity Knowledge Injection 1 1 23 Jul 2022 not harvested
Document-Level Relation Extraction with Structure Enhanced Transformer Encoder 0 1 11 Jul 2022 not harvested
Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction 1 1 28 May 2022 not harvested
Fine-grained Contrastive Learning for Relation Extraction 1 1 25 May 2022 not harvested
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning 0 1 21 May 2022 not harvested
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction 0 1 4 May 2022 not harvested
Few-Shot Document-Level Relation Extraction 1 1 4 May 2022 not harvested
Document-Level Relation Extraction with Sentences Importance Estimation and Focusing 1 1 27 Apr 2022 not harvested
A Masked Image Reconstruction Network for Document-level Relation Extraction 0 1 21 Apr 2022 not harvested
A sequence-to-sequence approach for document-level relation extraction 2 1 3 Apr 2022 not harvested
A Densely Connected Criss-Cross Attention Network for Document-level Relation Extraction 0 1 26 Mar 2022 not harvested
Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation 1 1 21 Mar 2022 not harvested
CorefDRE: Document-level Relation Extraction with coreference resolution 0 1 22 Feb 2022 not harvested
Document-level Relation Extraction with Context Guided Mention Integration and Inter-pair Reasoning 0 2 13 Jan 2022 not harvested
SagDRE: Sequence-Aware Graph-Based Document-Level Relation Extraction with Adaptive Margin Loss 1 1 16 Nov 2021 not harvested
Learning Logic Rules for Document-level Relation Extraction 1 2 9 Nov 2021 ran 0 of 3 samples (3 unverified)
REBEL: Relation Extraction By End-to-end Language generation 1 2 29 Oct 2021 not harvested
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction 1 2 24 Sep 2021 not harvested
MRN: A Locally and Globally Mention-Based Reasoning Network for Document-Level Relation Extraction 1 2 1 Aug 2021 not harvested
Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion 1 2 16 Jun 2021 not harvested
Document-level Relation Extraction as Semantic Segmentation 2 1 7 Jun 2021 not harvested
Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction 1 1 3 Jun 2021 ran 3 of 3 samples (0 unverified)
SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction 1 2 3 Jun 2021 not harvested
Discriminative Reasoning for Document-level Relation Extraction 2 2 3 Jun 2021 ran 8 of 10 samples (2 unverified)
Multi-view Inference for Relation Extraction with Uncertain Knowledge 1 1 28 Apr 2021 not harvested
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction 3 4 20 Feb 2021 not harvested
An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learning 1 2 11 Feb 2021 not harvested
Document-Level Relation Extraction with Reconstruction 1 2 21 Dec 2020 not harvested

The full list of 43 is in the JSON twin.

Dataset loaders archive 2025-07-28

3 loaders as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • DocRED

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections