| --- |
| dataset_info: |
| - config_name: ai |
| features: |
| - name: tokens |
| list: string |
| - name: ner_tags |
| list: string |
| splits: |
| - name: train |
| num_bytes: 63809 |
| num_examples: 100 |
| - name: validation |
| num_bytes: 182528 |
| num_examples: 350 |
| - name: test |
| num_bytes: 215707 |
| num_examples: 431 |
| download_size: 466273 |
| dataset_size: 462044 |
| - config_name: literature |
| features: |
| - name: tokens |
| list: string |
| - name: ner_tags |
| list: string |
| splits: |
| - name: train |
| num_bytes: 60068 |
| num_examples: 100 |
| - name: validation |
| num_bytes: 232541 |
| num_examples: 400 |
| - name: test |
| num_bytes: 255388 |
| num_examples: 416 |
| download_size: 552570 |
| dataset_size: 547997 |
| - config_name: music |
| features: |
| - name: tokens |
| list: string |
| - name: ner_tags |
| list: string |
| splits: |
| - name: train |
| num_bytes: 65506 |
| num_examples: 100 |
| - name: validation |
| num_bytes: 262527 |
| num_examples: 380 |
| - name: test |
| num_bytes: 331086 |
| num_examples: 465 |
| download_size: 663878 |
| dataset_size: 659119 |
| - config_name: politics |
| features: |
| - name: tokens |
| list: string |
| - name: ner_tags |
| list: string |
| splits: |
| - name: train |
| num_bytes: 149541 |
| num_examples: 200 |
| - name: validation |
| num_bytes: 455547 |
| num_examples: 541 |
| - name: test |
| num_bytes: 498599 |
| num_examples: 651 |
| download_size: 1108588 |
| dataset_size: 1103687 |
| - config_name: science |
| features: |
| - name: tokens |
| list: string |
| - name: ner_tags |
| list: string |
| splits: |
| - name: train |
| num_bytes: 123025 |
| num_examples: 200 |
| - name: validation |
| num_bytes: 287326 |
| num_examples: 450 |
| - name: test |
| num_bytes: 342508 |
| num_examples: 543 |
| download_size: 757370 |
| dataset_size: 752859 |
| configs: |
| - config_name: ai |
| data_files: |
| - split: train |
| path: ai/train-* |
| - split: validation |
| path: ai/validation-* |
| - split: test |
| path: ai/test-* |
| - config_name: literature |
| data_files: |
| - split: train |
| path: literature/train-* |
| - split: validation |
| path: literature/validation-* |
| - split: test |
| path: literature/test-* |
| - config_name: music |
| data_files: |
| - split: train |
| path: music/train-* |
| - split: validation |
| path: music/validation-* |
| - split: test |
| path: music/test-* |
| - config_name: politics |
| data_files: |
| - split: train |
| path: politics/train-* |
| - split: validation |
| path: politics/validation-* |
| - split: test |
| path: politics/test-* |
| - config_name: science |
| data_files: |
| - split: train |
| path: science/train-* |
| - split: validation |
| path: science/validation-* |
| - split: test |
| path: science/test-* |
| --- |
| |
| ai = ['ALGORITHM', 'CONFERENCE', 'COUNTRY', 'FIELD', 'LOCATION', 'METRIC', 'MISC', 'ORGANIZATION', 'PERSON', 'PRODUCT', 'PROGRAMMING_LANGUAGE', 'RESEARCHER', 'TASK', 'UNIVERSITY'] |
| |
| literature = ['AWARD', 'BOOK', 'COUNTRY', 'EVENT', 'LITERARY_GENRE', 'LOCATION', 'MAGAZINE', 'MISC', 'ORGANIZATION', 'PERSON', 'POEM', 'WRITER'] |
|
|
| music = ['ALBUM', 'AWARD', 'BAND', 'COUNTRY', 'EVENT', 'LOCATION', 'MISC', 'MUSICAL_ARTIST', 'MUSICAL_INSTRUMENT', 'MUSIC_GENRE', 'ORGANIZATION', 'PERSON', 'SONG'] |
| |
| politics = ['COUNTRY', 'ELECTION', 'EVENT', 'LOCATION', 'MISC', 'ORGANIZATION', 'PERSON', 'POLITICAL_PARTY', 'POLITICIAN'] |
|
|
| science = ['ACADEMIC_JOURNAL', 'ASTRONOMICAL_OBJECT', 'AWARD', 'CHEMICAL_COMPOUND', 'CHEMICAL_ELEMENT', 'COUNTRY', 'DISCIPLINE', 'ENZYME', 'EVENT', 'LOCATION', 'MISC', 'ORGANIZATION', 'PERSON', 'PROTEIN', 'SCIENTIST', 'THEORY', 'UNIVERSITY'] |