Datasets:
turkish_shrinked_ner

- {"default": {"description": "Shrinked version (48 entity type) of the turkish_ner.\n\nOriginal turkish_ner dataset: Automatically annotated Turkish corpus for named entity recognition and text categorization using large-scale gazetteers. The constructed gazetteers contains approximately 300K entities with thousands of fine-grained entity types under 25 different domains.\n\nShrinked entity types are: academic, academic_person, aircraft, album_person, anatomy, animal, architect_person, capital, chemical, clothes, country, culture, currency, date, food, genre, government, government_person, language, location, material, measure, medical, military, military_person, nation, newspaper, organization, organization_person, person, production_art_music, production_art_music_person, quantity, religion, science, shape, ship, software, space, space_person, sport, sport_name, sport_person, structure, subject, tech, train, vehicle\n", "citation": "", "homepage": "https://www.kaggle.com/behcetsenturk/shrinked-twnertc-turkish-ner-data-by-kuzgunlar", "license": "Attribution 4.0 International (CC BY 4.0)", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 97, "names": ["O", "B-academic", "I-academic", "B-academic_person", "I-academic_person", "B-aircraft", "I-aircraft", "B-album_person", "I-album_person", "B-anatomy", "I-anatomy", "B-animal", "I-animal", "B-architect_person", "I-architect_person", "B-capital", "I-capital", "B-chemical", "I-chemical", "B-clothes", "I-clothes", "B-country", "I-country", "B-culture", "I-culture", "B-currency", "I-currency", "B-date", "I-date", "B-food", "I-food", "B-genre", "I-genre", "B-government", "I-government", "B-government_person", "I-government_person", "B-language", "I-language", "B-location", "I-location", "B-material", "I-material", "B-measure", "I-measure", "B-medical", "I-medical", "B-military", "I-military", "B-military_person", "I-military_person", "B-nation", "I-nation", "B-newspaper", "I-newspaper", "B-organization", "I-organization", "B-organization_person", "I-organization_person", "B-person", "I-person", "B-production_art_music", "I-production_art_music", "B-production_art_music_person", "I-production_art_music_person", "B-quantity", "I-quantity", "B-religion", "I-religion", "B-science", "I-science", "B-shape", "I-shape", "B-ship", "I-ship", "B-software", "I-software", "B-space", "I-space", "B-space_person", "I-space_person", "B-sport", "I-sport", "B-sport_name", "I-sport_name", "B-sport_person", "I-sport_person", "B-structure", "I-structure", "B-subject", "I-subject", "B-tech", "I-tech", "B-train", "I-train", "B-vehicle", "I-vehicle"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "turkish_shrinked_ner", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 200728389, "num_examples": 614515, "dataset_name": "turkish_shrinked_ner"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 200728389, "size_in_bytes": 200728389}}