{
 "id": "microsoft/SYNUR",
 "owner": "microsoft",
 "name": "SYNUR",
 "downloads": 264,
 "likes": 10,
 "last_modified": "2026-03-02T21:26:58.000Z",
 "stated_licence": "cdla-permissive-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-generation",
  "token-classification"
 ],
 "citation": "If you use the original split and MEDIQA-SYNUR splits, please cite the papers below:\n\n    @inproceedings{corbeil-etal-2025-empowering,\n        title = \"Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications\",\n        author = \"Corbeil, Jean-Philippe  and\n          Ben Abacha, Asma  and\n          Michalopoulos, George  and\n          Swazinna, Phillip  and\n          Del-Agua, Miguel  and\n          Tremblay, Jerome  and\n          Daniel, Akila Jeeson  and\n          Bader, Cari  and\n          Cho, Kevin  and\n          Krishnan, Pooja  and\n          Bodenstab, Nathan  and\n          Lin, Thomas  and\n          Teng, Wenxuan  and\n          Beaulieu, Francois  and\n          Vozila, Paul\",\n        editor = \"Potdar, Saloni  and\n          Rojas-Barahona, Lina  and\n          Montella, Sebastien\",\n        booktitle = \"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track\",\n        month = nov,\n        year = \"2025\",\n        address = \"Suzhou (China)\",\n        publisher = \"Association for Computational Linguistics\",\n        url = \"https://aclanthology.org/2025.emnlp-industry.58/\",\n        doi = \"10.18653/v1/2025.emnlp-industry.58\",\n        pages = \"859--870\",\n        ISBN = \"979-8-89176-333-3\"\n    }\n\n    @inproceedings{mediqa-synur-task,\n      author    = {George Michalopoulos, Jean{-}Philippe Corbeil, Cari Bader, Nate Bodenstab, Asma {Ben Abacha}},\n      title     = {O",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "c7f79af4dcc8e5fb175c40cef0592d85a76bf11c",
 "stated_evidence": "https://huggingface.co/datasets/microsoft/SYNUR/blob/c7f79af4dcc8e5fb175c40cef0592d85a76bf11c/README.md",
 "file_evidence": "https://huggingface.co/datasets/microsoft/SYNUR/tree/c7f79af4dcc8e5fb175c40cef0592d85a76bf11c",
 "card_nc": false
}