Datasets › NYT-H

NYT-H

Introduced by Tong Zhu et al. in Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction30 Oct 2020 archive 2025-07-28

NYT-H is a dataset for distantly-supervised relation extraction, in which DS-labelled training data is used and several annotators to label test data are hired. NYT-H can serve as a benchmark of distantly-supervised relation extraction.

Source: Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction

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 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

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

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • NYT-H

1 variant name, as the archive lists them.

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