Datasets › CodRED

CodRED

Introduced by Yuan YAO et al. in CodRED: A Cross-Document Relation Extraction Dataset for Acquiring Knowledge in the Wild1 Nov 2021 archive 2025-07-28

CodRED is the first human-annotated cross-document relation extraction (RE) dataset, aiming to test the RE systems’ ability of knowledge acquisition in the wild. CodRED has the following features:

  • it requires natural language understanding in different granularity, including coarse-grained document retrieval, as well as fine-grained cross-document multi-hop reasoning;

  • it contains 30,504 relational facts associated with 210,812 reasoning text paths, as well as enjoys a broad range of balanced relations, and long documents in diverse topics;

  • it provides strong supervision about the reasoning text paths for predicting the relation, to help guide RE systems to perform meaningful and interpretable reasoning;

  • it contains adversarially-created hard NA instances to avoid RE models to predict relations by inferring from entity names instead of text information.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 5 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

MIT

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • CodRED

1 variant name, as the archive lists them.

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