Datasets:

grit-id
/

id_nergrit_corpus

- {"ner": {"description": "Nergrit Corpus is a dataset collection for Indonesian Named Entity Recognition, Statement Extraction, and Sentiment\nAnalysis. id_nergrit_corpus is the Named Entity Recognition of this dataset collection which contains 18 entities as\nfollow:\n 'CRD': Cardinal\n 'DAT': Date\n 'EVT': Event\n 'FAC': Facility\n 'GPE': Geopolitical Entity\n 'LAW': Law Entity (such as Undang-Undang)\n 'LOC': Location\n 'MON': Money\n 'NOR': Political Organization\n 'ORD': Ordinal\n 'ORG': Organization\n 'PER': Person\n 'PRC': Percent\n 'PRD': Product\n 'QTY': Quantity\n 'REG': Religion\n 'TIM': Time\n 'WOA': Work of Art\n 'LAN': Language\n", "citation": "@inproceedings{id_nergrit_corpus,\n author = {Gria Inovasi Teknologi},\n title = {NERGRIT CORPUS},\n year = {2019},\n url = {https://github.com/grit-id/nergrit-corpus},\n}\n", "homepage": "https://github.com/grit-id/nergrit-corpus", "license": "", "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": 39, "names": ["B-CRD", "B-DAT", "B-EVT", "B-FAC", "B-GPE", "B-LAN", "B-LAW", "B-LOC", "B-MON", "B-NOR", "B-ORD", "B-ORG", "B-PER", "B-PRC", "B-PRD", "B-QTY", "B-REG", "B-TIM", "B-WOA", "I-CRD", "I-DAT", "I-EVT", "I-FAC", "I-GPE", "I-LAN", "I-LAW", "I-LOC", "I-MON", "I-NOR", "I-ORD", "I-ORG", "I-PER", "I-PRC", "I-PRD", "I-QTY", "I-REG", "I-TIM", "I-WOA", "O"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "id_nergrit_corpus", "config_name": "ner", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5428411, "num_examples": 12532, "dataset_name": "id_nergrit_corpus"}, "test": {"name": "test", "num_bytes": 1135577, "num_examples": 2399, "dataset_name": "id_nergrit_corpus"}, "validation": {"name": "validation", "num_bytes": 1086437, "num_examples": 2521, "dataset_name": "id_nergrit_corpus"}}, "download_checksums": {"https://github.com/cahya-wirawan/indonesian-language-models/raw/master/data/nergrit-corpus_20190726_corrected.tgz": {"num_bytes": 14988232, "checksum": "ac53b61612d6d53c8c800a67d70b6b800f662ab7029aa622163834945efa85d6"}}, "download_size": 14988232, "post_processing_size": null, "dataset_size": 7650425, "size_in_bytes": 22638657}, "sentiment": {"description": "Nergrit Corpus is a dataset collection for Indonesian Named Entity Recognition, Statement Extraction, and Sentiment\nAnalysis. id_nergrit_corpus is the Named Entity Recognition of this dataset collection which contains 18 entities as\nfollow:\n 'CRD': Cardinal\n 'DAT': Date\n 'EVT': Event\n 'FAC': Facility\n 'GPE': Geopolitical Entity\n 'LAW': Law Entity (such as Undang-Undang)\n 'LOC': Location\n 'MON': Money\n 'NOR': Political Organization\n 'ORD': Ordinal\n 'ORG': Organization\n 'PER': Person\n 'PRC': Percent\n 'PRD': Product\n 'QTY': Quantity\n 'REG': Religion\n 'TIM': Time\n 'WOA': Work of Art\n 'LAN': Language\n", "citation": "@inproceedings{id_nergrit_corpus,\n author = {Gria Inovasi Teknologi},\n title = {NERGRIT CORPUS},\n year = {2019},\n url = {https://github.com/grit-id/nergrit-corpus},\n}\n", "homepage": "https://github.com/grit-id/nergrit-corpus", "license": "", "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": 7, "names": ["B-NEG", "B-NET", "B-POS", "I-NEG", "I-NET", "I-POS", "O"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "id_nergrit_corpus", "config_name": "sentiment", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3167972, "num_examples": 7485, "dataset_name": "id_nergrit_corpus"}, "test": {"name": "test", "num_bytes": 1097517, "num_examples": 2317, "dataset_name": "id_nergrit_corpus"}, "validation": {"name": "validation", "num_bytes": 337679, "num_examples": 782, "dataset_name": "id_nergrit_corpus"}}, "download_checksums": {"https://github.com/cahya-wirawan/indonesian-language-models/raw/master/data/nergrit-corpus_20190726_corrected.tgz": {"num_bytes": 14988232, "checksum": "ac53b61612d6d53c8c800a67d70b6b800f662ab7029aa622163834945efa85d6"}}, "download_size": 14988232, "post_processing_size": null, "dataset_size": 4603168, "size_in_bytes": 19591400}, "statement": {"description": "Nergrit Corpus is a dataset collection for Indonesian Named Entity Recognition, Statement Extraction, and Sentiment\nAnalysis. id_nergrit_corpus is the Named Entity Recognition of this dataset collection which contains 18 entities as\nfollow:\n 'CRD': Cardinal\n 'DAT': Date\n 'EVT': Event\n 'FAC': Facility\n 'GPE': Geopolitical Entity\n 'LAW': Law Entity (such as Undang-Undang)\n 'LOC': Location\n 'MON': Money\n 'NOR': Political Organization\n 'ORD': Ordinal\n 'ORG': Organization\n 'PER': Person\n 'PRC': Percent\n 'PRD': Product\n 'QTY': Quantity\n 'REG': Religion\n 'TIM': Time\n 'WOA': Work of Art\n 'LAN': Language\n", "citation": "@inproceedings{id_nergrit_corpus,\n author = {Gria Inovasi Teknologi},\n title = {NERGRIT CORPUS},\n year = {2019},\n url = {https://github.com/grit-id/nergrit-corpus},\n}\n", "homepage": "https://github.com/grit-id/nergrit-corpus", "license": "", "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": 9, "names": ["B-BREL", "B-FREL", "B-STAT", "B-WHO", "I-BREL", "I-FREL", "I-STAT", "I-WHO", "O"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "id_nergrit_corpus", "config_name": "statement", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1469081, "num_examples": 2405, "dataset_name": "id_nergrit_corpus"}, "test": {"name": "test", "num_bytes": 182553, "num_examples": 335, "dataset_name": "id_nergrit_corpus"}, "validation": {"name": "validation", "num_bytes": 105119, "num_examples": 176, "dataset_name": "id_nergrit_corpus"}}, "download_checksums": {"https://github.com/cahya-wirawan/indonesian-language-models/raw/master/data/nergrit-corpus_20190726_corrected.tgz": {"num_bytes": 14988232, "checksum": "ac53b61612d6d53c8c800a67d70b6b800f662ab7029aa622163834945efa85d6"}}, "download_size": 14988232, "post_processing_size": null, "dataset_size": 1756753, "size_in_bytes": 16744985}}