{
 "id": "alexandrainst/dane",
 "owner": "alexandrainst",
 "name": "dane",
 "downloads": 529,
 "likes": 10,
 "last_modified": "2024-01-18T11:02:29.000Z",
 "stated_licence": "cc-by-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [
  {
   "id": "other-Danish-Universal-Dependencies-treebank",
   "licence": null,
   "found": false,
   "evidence": "https://huggingface.co/datasets/other-Danish-Universal-Dependencies-treebank"
  }
 ],
 "gated": false,
 "tasks": [
  "token-classification"
 ],
 "citation": "@inproceedings{hvingelby-etal-2020-dane,\n    title = \"{D}a{NE}: A Named Entity Resource for {D}anish\",\n    author = \"Hvingelby, Rasmus  and\n      Pauli, Amalie Brogaard  and\n      Barrett, Maria  and\n      Rosted, Christina  and\n      Lidegaard, Lasse Malm  and\n      S{\\o}gaard, Anders\",\n    booktitle = \"Proceedings of the 12th Language Resources and Evaluation Conference\",\n    month = may,\n    year = \"2020\",\n    address = \"Marseille, France\",\n    publisher = \"European Language Resources Association\",\n    url = \"https://aclanthology.org/2020.lrec-1.565\",\n    pages = \"4597--4604\",\n    abstract = \"We present a named entity annotation for the Danish Universal Dependencies treebank using the CoNLL-2003 annotation scheme: DaNE. It is the largest publicly available, Danish named entity gold annotation. We evaluate the quality of our annotations intrinsically by double annotating the entire treebank and extrinsically by comparing our annotations to a recently released named entity annotation of the validation and test sections of the Danish Universal Dependencies treebank. We benchmark the new resource by training and evaluating competitive architectures for supervised named entity recognition (NER), including FLAIR, monolingual (Danish) BERT and multilingual BERT. We explore cross-lingual transfer in multilingual BERT from five related languages in zero-shot and direct transfer setups, and we show that even with our modestly-sized training set, we improve Danish NER over a recent c",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID for at least one declared source dataset.",
 "revision": "f303de644792372c0a24869c165f500e6f5c45fb",
 "stated_evidence": "https://huggingface.co/datasets/alexandrainst/dane/blob/f303de644792372c0a24869c165f500e6f5c45fb/README.md",
 "file_evidence": "https://huggingface.co/datasets/alexandrainst/dane/tree/f303de644792372c0a24869c165f500e6f5c45fb",
 "card_nc": false
}