{
 "id": "B1tta/Drug-ACE",
 "owner": "B1tta",
 "name": "Drug-ACE",
 "downloads": 28,
 "likes": 0,
 "last_modified": "2026-07-01T06:51:46.000Z",
 "stated_licence": "apache-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-classification"
 ],
 "citation": "If you find our paper, code, or dataset helpful, please consider citing our work:\n\n```bibtex\n@inproceedings{luo-etal-2026-applicability,\n    title = \"Applicability Condition Extraction for Therapeutic Drug-Disease Relations\",\n    author = \"Luo, Guanting  and\n      Nishida, Noriki  and\n      Matsumoto, Yuji  and\n      Arase, Yuki\",\n    editor = \"Liakata, Maria  and\n      Moreira, Viviane P.  and\n      Zhang, Jiajun  and\n      Jurgens, David\",\n    booktitle = \"Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026\",\n    month = jul,\n    year = \"2026\",\n    address = \"San Diego, California, United States\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2026.findings-acl.154/\",\n    pages = \"3135--3148\",\n    ISBN = \"979-8-89176-395-1\",\n    abstract = \"Identifying conditions that a certain drug takes therapeutic effect on a target disease is crucial for clinical decision-making support. However, most existing biomedical information extraction methods have focused on identifying only relations between drugs and diseases, while largely overlooking the context-specific conditions where such relations can apply. To address this problem, we introduce the task of applicability condition extraction for therapeutic drug{--}disease relations from biomedical research literature. We create the first dataset that has manually annotated triples of drugs, diseases, and applicability conditions on biomedical paper abstracts wit",
 "signal": "permissive",
 "reason": "The declared licence (apache-2.0) is classified as permissive.",
 "revision": "77125c938ab5a1b62c3d6f2dd7772efe189a133c",
 "stated_evidence": "https://huggingface.co/datasets/B1tta/Drug-ACE/blob/77125c938ab5a1b62c3d6f2dd7772efe189a133c/README.md",
 "file_evidence": "https://huggingface.co/datasets/B1tta/Drug-ACE/tree/77125c938ab5a1b62c3d6f2dd7772efe189a133c",
 "card_nc": false
}