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Dataset Card for turkish_ner
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.
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