README.md

metadata

annotations_creators:
  - machine-generated
language_creators:
  - expert-generated
language:
  - tr
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 100K<n<1M
source_datasets:
  - original
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
pretty_name: TurkishNer
dataset_info:
  features:
    - name: id
      dtype: string
    - name: tokens
      sequence: string
    - name: domain
      dtype:
        class_label:
          names:
            '0': architecture
            '1': basketball
            '2': book
            '3': business
            '4': education
            '5': fictional_universe
            '6': film
            '7': food
            '8': geography
            '9': government
            '10': law
            '11': location
            '12': military
            '13': music
            '14': opera
            '15': organization
            '16': people
            '17': religion
            '18': royalty
            '19': soccer
            '20': sports
            '21': theater
            '22': time
            '23': travel
            '24': tv
    - name: ner_tags
      sequence:
        class_label:
          names:
            '0': O
            '1': B-PERSON
            '2': I-PERSON
            '3': B-ORGANIZATION
            '4': I-ORGANIZATION
            '5': B-LOCATION
            '6': I-LOCATION
            '7': B-MISC
            '8': I-MISC
  splits:
    - name: train
      num_bytes: 177658278
      num_examples: 532629
  download_size: 204393976
  dataset_size: 177658278

Dataset Card for turkish_ner

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: http://arxiv.org/abs/1702.02363
• Repository: [Needs More Information]
• Paper: http://arxiv.org/abs/1702.02363
• Leaderboard: [Needs More Information]
• Point of Contact: [email protected]

Dataset Summary

Automatically annotated Turkish corpus for named entity recognition and text categorization using large-scale gazetteers. The constructed gazetteers contains approximately 300K entities with thousands of fine-grained entity types under 25 different domains.

Supported Tasks and Leaderboards

[Needs More Information]

Languages

Turkish

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

There's only the training set.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

H. Bahadir Sahin, Caglar Tirkaz, Eray Yildiz, Mustafa Tolga Eren and Omer Ozan Sonmez

Licensing Information

Creative Commons Attribution 4.0 International

Citation Information

@InProceedings@article{DBLP:journals/corr/SahinTYES17, author = {H. Bahadir Sahin and Caglar Tirkaz and Eray Yildiz and Mustafa Tolga Eren and Omer Ozan Sonmez}, title = {Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers}, journal = {CoRR}, volume = {abs/1702.02363}, year = {2017}, url = {http://arxiv.org/abs/1702.02363}, archivePrefix = {arXiv}, eprint = {1702.02363}, timestamp = {Mon, 13 Aug 2018 16:46:36 +0200}, biburl = {https://dblp.org/rec/journals/corr/SahinTYES17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }

Contributions

Thanks to @merveenoyan for adding this dataset.