Datasets:
annotations_creators:
- machine-generated
language_creators:
- expert-generated
language:
- tr
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- extended|other-turkish_ner
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: TurkishShrinkedNer
dataset_info:
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-academic
'2': I-academic
'3': B-academic_person
'4': I-academic_person
'5': B-aircraft
'6': I-aircraft
'7': B-album_person
'8': I-album_person
'9': B-anatomy
'10': I-anatomy
'11': B-animal
'12': I-animal
'13': B-architect_person
'14': I-architect_person
'15': B-capital
'16': I-capital
'17': B-chemical
'18': I-chemical
'19': B-clothes
'20': I-clothes
'21': B-country
'22': I-country
'23': B-culture
'24': I-culture
'25': B-currency
'26': I-currency
'27': B-date
'28': I-date
'29': B-food
'30': I-food
'31': B-genre
'32': I-genre
'33': B-government
'34': I-government
'35': B-government_person
'36': I-government_person
'37': B-language
'38': I-language
'39': B-location
'40': I-location
'41': B-material
'42': I-material
'43': B-measure
'44': I-measure
'45': B-medical
'46': I-medical
'47': B-military
'48': I-military
'49': B-military_person
'50': I-military_person
'51': B-nation
'52': I-nation
'53': B-newspaper
'54': I-newspaper
'55': B-organization
'56': I-organization
'57': B-organization_person
'58': I-organization_person
'59': B-person
'60': I-person
'61': B-production_art_music
'62': I-production_art_music
'63': B-production_art_music_person
'64': I-production_art_music_person
'65': B-quantity
'66': I-quantity
'67': B-religion
'68': I-religion
'69': B-science
'70': I-science
'71': B-shape
'72': I-shape
'73': B-ship
'74': I-ship
'75': B-software
'76': I-software
'77': B-space
'78': I-space
'79': B-space_person
'80': I-space_person
'81': B-sport
'82': I-sport
'83': B-sport_name
'84': I-sport_name
'85': B-sport_person
'86': I-sport_person
'87': B-structure
'88': I-structure
'89': B-subject
'90': I-subject
'91': B-tech
'92': I-tech
'93': B-train
'94': I-train
'95': B-vehicle
'96': I-vehicle
splits:
- name: train
num_bytes: 200728389
num_examples: 614515
download_size: 0
dataset_size: 200728389
Dataset Card for turkish_shrinked_ner
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://www.kaggle.com/behcetsenturk/shrinked-twnertc-turkish-ner-data-by-kuzgunlar
- Repository: [Needs More Information]
- Paper: [Needs More Information]
- Leaderboard: [Needs More Information]
- Point of Contact: https://www.kaggle.com/behcetsenturk
Dataset Summary
Shrinked processed version (48 entity type) of the turkish_ner.
Original turkish_ner dataset: 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.
Shrinked entity types are: academic, academic_person, aircraft, album_person, anatomy, animal, architect_person, capital, chemical, clothes, country, culture, currency, date, food, genre, government, government_person, language, location, material, measure, medical, military, military_person, nation, newspaper, organization, organization_person, person, production_art_music, production_art_music_person, quantity, religion, science, shape, ship, software, space, space_person, sport, sport_name, sport_person, structure, subject, tech, train, vehicle
Supported Tasks and Leaderboards
[Needs More Information]
Languages
Turkish
Dataset Structure
Data Instances
[Needs More Information]
Data Fields
[Needs More Information]
Data Splits
There's only the training set.
Dataset Creation
Curation Rationale
[Needs More Information]
Source Data
Initial Data Collection and Normalization
[Needs More Information]
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
[Needs More Information]
Personal and Sensitive Information
[Needs More Information]
Considerations for Using the Data
Social Impact of Dataset
[Needs More Information]
Discussion of Biases
[Needs More Information]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
Behcet Senturk
Licensing Information
Creative Commons Attribution 4.0 International
Citation Information
[Needs More Information]
Contributions
Thanks to @bhctsntrk for adding this dataset.