Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Turkish
Size:
100K<n<1M
ArXiv:
License:
File size: 5,069 Bytes
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---
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-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#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:** erayyildiz@ktu.edu.tr
### 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](https://github.com/merveenoyan) for adding this dataset. |