metadata

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.

This repository is merely made to simplify the workflow. Previous version of the dataset was published in a similar fashion at benjamin/ner-uk.

License

"Корпус NER-анотацій українських текстів" by lang-uk is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Based on a work at 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."
}