Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Languages:
Vietnamese
Size:
10K - 100K
Tags:
legal
| task_categories: | |
| - token-classification | |
| language: | |
| - vi | |
| tags: | |
| - legal | |
| size_categories: | |
| - 10K<n<100K | |
| ## Vi-Ner | |
| ### Dataset Description | |
| ner_tags: a list of classification labels (int). Full tagset with indices: | |
| ```python | |
| {'B-DATETIME': 0, | |
| 'B-LOCATION': 1, | |
| 'B-ORGANIZATION': 2, | |
| 'B-PERSON': 3, | |
| 'I-DATETIME': 4, | |
| 'I-LOCATION': 5, | |
| 'I-ORGANIZATION': 6, | |
| 'I-PERSON': 7, | |
| 'O': 8} | |
| ``` | |
| ### Data Splits | |
| | name |train|validation|test| | |
| |---------|----:|---------:|---:| | |
| | Vi-Ner |19255| 2407|2407| | |
| ### Example | |
| An example of 'train' looks as follows. | |
| ``` | |
| { | |
| {'tokens': ['NSƯT', 'Hồng', 'Liên', '(trái)', 'đến', 'chúc', 'mừng', 'Thu', 'Trang..'], | |
| 'ner_tags': ['B-PERSON', 'I-PERSON', 'I-PERSON', 'O', 'O', 'O', 'O', 'B-PERSON', 'I-PERSON'], | |
| 'ner_idx': [3, 7, 7, 8, 8, 8, 8, 3, 7]} | |
| } | |
| ``` | |
| ### Usage | |
| ```python | |
| import datasets | |
| vi_ner = datasets.load_dataset('Minggz/Vi-Ner') | |
| vi_ner | |
| ``` |