language: ru | |
multilinguality: monolingual | |
task_ids: | |
- named-entity-recognition | |
### About DataSet | |
The dataset based on NEREL corpus. | |
For more information about original data, please visit this [source](https://github.com/dialogue-evaluation/RuNNE) | |
Example of preparing original data illustrated in <Prepare_original_data.ipynb> | |
### Additional info | |
The dataset consist 29 entities, each of them can be as beginner part of entity "B-" as inner "I-". | |
Frequency for each entity: | |
- I-AGE: 284 | |
- B-AGE: 247 | |
- B-AWARD: 285 | |
- I-AWARD: 466 | |
- B-CITY: 1080 | |
- I-CITY: 39 | |
- B-COUNTRY: 2378 | |
- I-COUNTRY: 128 | |
- B-CRIME: 214 | |
- I-CRIME: 372 | |
- B-DATE: 2701 | |
- I-DATE: 5437 | |
- B-DISEASE: 136 | |
- I-DISEASE: 80 | |
- B-DISTRICT: 98 | |
- I-DISTRICT: 73 | |
- B-EVENT: 3369 | |
- I-EVENT: 2524 | |
- B-FACILITY: 376 | |
- I-FACILITY: 510 | |
- B-FAMILY: 27 | |
- I-FAMILY: 22 | |
- B-IDEOLOGY: 271 | |
- I-IDEOLOGY: 20 | |
- B-LANGUAGE: 32 | |
- I-LAW: 1196 | |
- B-LAW: 297 | |
- B-LOCATION: 242 | |
- I-LOCATION: 139 | |
- B-MONEY: 147 | |
- I-MONEY: 361 | |
- B-NATIONALITY: 437 | |
- I-NATIONALITY: 41 | |
- B-NUMBER: 1079 | |
- I-NUMBER: 328 | |
- B-ORDINAL: 485 | |
- I-ORDINAL: 6 | |
- B-ORGANIZATION: 3339 | |
- I-ORGANIZATION: 3354 | |
- B-PENALTY: 73 | |
- I-PENALTY: 104 | |
- B-PERCENT: 51 | |
- I-PERCENT: 37 | |
- B-PERSON: 5148 | |
- I-PERSON: 3635 | |
- I-PRODUCT: 48 | |
- B-PRODUCT: 197 | |
- B-PROFESSION: 3869 | |
- I-PROFESSION: 2598 | |
- B-RELIGION: 102 | |
- I-RELIGION: 1 | |
- B-STATE_OR_PROVINCE: 436 | |
- I-STATE_OR_PROVINCE: 154 | |
- B-TIME: 187 | |
- I-TIME: 529 | |
- B-WORK_OF_ART: 133 | |
- I-WORK_OF_ART: 194 | |
You can find mapper for entity ids in <id_to_label_map.pickle> file: | |
```python | |
import pickle | |
with open('id_to_label_map.pickle', 'rb') as f: | |
mapper = pickle.load(f) | |
``` |