| {"default": {"description": "We describe a dataset developed for Named Entity Recognition in German federal court decisions. \nIt consists of approx. 67,000 sentences with over 2 million tokens. \nThe resource contains 54,000 manually annotated entities, mapped to 19 fine-grained semantic classes: \nperson, judge, lawyer, country, city, street, landscape, organization, company, institution, court, brand, law, \nordinance, European legal norm, regulation, contract, court decision, and legal literature. \nThe legal documents were, furthermore, automatically annotated with more than 35,000 TimeML-based time expressions. \nThe dataset, which is available under a CC-BY 4.0 license in the CoNNL-2002 format, \nwas developed for training an NER service for German legal documents in the EU project Lynx.\n", "citation": "@inproceedings{leitner2019fine,\n author = {Elena Leitner and Georg Rehm and Julian Moreno-Schneider},\n title = {{Fine-grained Named Entity Recognition in Legal Documents}},\n booktitle = {Semantic Systems. The Power of AI and Knowledge\n Graphs. Proceedings of the 15th International Conference\n (SEMANTiCS 2019)},\n year = 2019,\n editor = {Maribel Acosta and Philippe Cudr\u00e9-Mauroux and Maria\n Maleshkova and Tassilo Pellegrini and Harald Sack and York\n Sure-Vetter},\n keywords = {aip},\n publisher = {Springer},\n series = {Lecture Notes in Computer Science},\n number = {11702},\n address = {Karlsruhe, Germany},\n month = 9,\n note = {10/11 September 2019},\n pages = {272--287},\n pdf = {https://link.springer.com/content/pdf/10.1007%2F978-3-030-33220-4_20.pdf}\n}\n", "homepage": "https://github.com/elenanereiss/Legal-Entity-Recognition", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 39, "names": ["O", "B-PER", "I-PER", "B-RR", "I-RR", "B-AN", "I-AN", "B-LD", "I-LD", "B-ST", "I-ST", "B-STR", "I-STR", "B-LDS", "I-LDS", "B-ORG", "I-ORG", "B-UN", "I-UN", "B-INN", "I-INN", "B-GRT", "I-GRT", "B-MRK", "I-MRK", "B-GS", "I-GS", "B-VO", "I-VO", "B-EUN", "I-EUN", "B-VS", "I-VS", "B-VT", "I-VT", "B-RS", "I-RS", "B-LIT", "I-LIT"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": {"input": "tokens", "output": "ner_tags"}, "builder_name": "ler", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 38531395, "num_examples": 66723, "dataset_name": "ler"}}, "download_checksums": {"https://raw.githubusercontent.com/elenanereiss/Legal-Entity-Recognition/master/data/ler.conll": {"num_bytes": 19692859, "checksum": "b05bf29720519d3d4a871677189035390607140887e871e30e8abc68ed01581f"}}, "download_size": 19692859, "post_processing_size": null, "dataset_size": 38531395, "size_in_bytes": 58224254}} |