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DFKI-SLT/MedDistant19

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Unclear

The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: other, from the tagEvidence: README.md at 5c1ddd8
Licence files: No licence file at the top level of the repositoryEvidence: file list at 5c1ddd8
Declared sources: 2
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Sources listed in the card metadata

PubMedotherUnclearEvidence: README.md at 8263182
UMLSnot foundUnclearEvidence: Hub page

Tasks

text-classification

Citation text from the card

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

```tex
@inproceedings{amin-etal-2022-meddistant19,
    title = "{M}ed{D}istant19: Towards an Accurate Benchmark for Broad-Coverage Biomedical Relation Extraction",
    author = "Amin, Saadullah and Minervini, Pasquale and Chang, David and Stenetorp, Pontus and Neumann, G{\"u}nter",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2022.coling-1.198",
    pages = "2259--2277",
}
```

**APA:**

Amin, S., Minervini, P., Chang, D., Stenetorp, P., & Neumann, G. (2022). Meddistant19: towards an accurate benchmark for broad-coverage biomedical relation extraction. arXiv preprint arXiv:2204.04779.

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dataset_licence({ "id": "DFKI-SLT/MedDistant19" })
signal: "unclear"
stated_licence: "other"
sources: 2