community-datasets/turkish_shrinked_ner
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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:
- 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-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:** 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](https://github.com/bhctsntrk) for adding this dataset.
提供机构：
community-datasets
原始信息汇总
数据集概述
数据集描述
数据集摘要
TurkishShrinkedNer 是一个经过处理的土耳其命名实体识别（NER）数据集的缩减版本，包含48种实体类型。原始数据集是通过大规模地名词典自动标注的土耳其语语料库，用于命名实体识别和文本分类。构建的地名词典包含大约300,000个实体，涵盖数千种细粒度实体类型，分布在25个不同领域。
支持的任务和排行榜
[需要更多信息]
语言
土耳其语
数据集结构
数据实例
[需要更多信息]
数据字段
- id: 字符串类型
- tokens: 字符串序列
- ner_tags: 标签序列，包含以下类别：
- 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
数据分割
数据集仅包含训练集，包含614,515个样本，总大小为200,728,389字节。
数据集创建
策划理由
[需要更多信息]
源数据
初始数据收集和规范化
[需要更多信息]
源语言生产者
[需要更多信息]
标注
标注过程
[需要更多信息]
标注者
[需要更多信息]
个人和敏感信息
[需要更多信息]
使用数据的注意事项
数据集的社会影响
[需要更多信息]
偏见的讨论
[需要更多信息]
其他已知限制
[需要更多信息]
附加信息
数据集策展人
Behcet Senturk
许可信息
Creative Commons Attribution 4.0 International
引用信息
[需要更多信息]
贡献
感谢 @bhctsntrk 添加此数据集。
