---
language:
- uk
license: cc-by-nc-sa-4.0
dataset_info:
  features:
  - name: document_id
    dtype: string
  - name: tokens
    sequence: string
  - name: ner_tags
    sequence:
      class_label:
        names:
          '0': O
          '1': B-ORG
          '2': I-ORG
          '3': B-PERS
          '4': I-PERS
          '5': B-LOC
          '6': I-LOC
          '7': B-MON
          '8': I-MON
          '9': B-PCT
          '10': I-PCT
          '11': B-DATE
          '12': I-DATE
          '13': B-TIME
          '14': I-TIME
          '15': B-PERIOD
          '16': I-PERIOD
          '17': B-JOB
          '18': I-JOB
          '19': B-DOC
          '20': I-DOC
          '21': B-QUANT
          '22': I-QUANT
          '23': B-ART
          '24': I-ART
          '25': B-MISC
          '26': I-MISC
  - name: source
    dtype: string
  splits:
  - name: train
    num_bytes: 4426002
    num_examples: 10980
  - name: validation
    num_bytes: 472074
    num_examples: 1206
  - name: test
    num_bytes: 2307876
    num_examples: 5593
  download_size: 1855779
  dataset_size: 7205952
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
task_categories:
- token-classification
---

# NER-UK 2.0


Second version of the Named Entity Recognition for Ukrainian dataset.

All the credit belongs to [lang-uk](https://github.com/lang-uk).

This repository is merely made to simplify the workflow. Previous version of the dataset was published in a similar fashion at [benjamin/ner-uk](https://huggingface.co/datasets/benjamin/ner-uk).

## License

<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a>

"Корпус NER-анотацій українських текстів" by [lang-uk](https://github.com/lang-uk) is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/).
Based on a work at [https://github.com/lang-uk/ner-uk](https://github.com/lang-uk/ner-uk).

## Citation

```
@inproceedings{chaplynskyi-romanyshyn-2024-introducing,
    title = "Introducing {NER}-{UK} 2.0: A Rich Corpus of Named Entities for {U}krainian",
    author = "Chaplynskyi, Dmytro  and
      Romanyshyn, Mariana",
    editor = "Romanyshyn, Mariana  and
      Romanyshyn, Nataliia  and
      Hlybovets, Andrii  and
      Ignatenko, Oleksii",
    booktitle = "Proceedings of the Third Ukrainian Natural Language Processing Workshop (UNLP) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.unlp-1.4/",
    pages = "23--29",
    abstract = "This paper presents NER-UK 2.0, a corpus of texts in the Ukrainian language manually annotated for the named entity recognition task. The corpus contains 560 texts of multiple genres, boasting 21,993 entities in total. The annotation scheme covers 13 entity types, namely location, person name, organization, artifact, document, job title, date, time, period, money, percentage, quantity, and miscellaneous. Such a rich set of entities makes the corpus valuable for training named-entity recognition models in various domains, including news, social media posts, legal documents, and procurement contracts. The paper presents an updated baseline solution for named entity recognition in Ukrainian with 0.89 F1. The corpus is the largest of its kind for the Ukrainian language and is available for download."
}
```