Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: CANER
dataset_info:
features:
- name: token
dtype: string
- name: ner_tag
dtype:
class_label:
names:
'0': Allah
'1': Book
'2': Clan
'3': Crime
'4': Date
'5': Day
'6': Hell
'7': Loc
'8': Meas
'9': Mon
'10': Month
'11': NatOb
'12': Number
'13': O
'14': Org
'15': Para
'16': Pers
'17': Prophet
'18': Rlig
'19': Sect
'20': Time
splits:
- name: train
num_bytes: 5095617
num_examples: 258240
download_size: 1459014
dataset_size: 5095617
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Dataset Card for CANER
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository: Classical-Arabic-Named-Entity-Recognition-Corpus
- Paper: Researchgate
- Leaderboard:
- Point of Contact:
Dataset Summary
The Classical Arabic Named Entity Recognition corpus is a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.
Supported Tasks and Leaderboards
- Named Entity Recognition
Languages
Classical Arabic
Dataset Structure
Data Instances
An example from the dataset:
{'ner_tag': 1, 'token': 'الجامع'}
Where 1 stands for "Book"
Data Fields
id
: id of the sampletoken
: the tokens of the example textner_tag
: the NER tags of each token
The NER tags correspond to this list:
"Allah",
"Book",
"Clan",
"Crime",
"Date",
"Day",
"Hell",
"Loc",
"Meas",
"Mon",
"Month",
"NatOb",
"Number",
"O",
"Org",
"Para",
"Pers",
"Prophet",
"Rlig",
"Sect",
"Time"
Data Splits
Training splits only
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?
Ramzi Salah and Lailatul Qadri Zakaria
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
[More Information Needed]
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@article{article, author = {Salah, Ramzi and Zakaria, Lailatul}, year = {2018}, month = {12}, pages = {}, title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)}, volume = {96}, journal = {Journal of Theoretical and Applied Information Technology} }
Contributions
Thanks to @KMFODA for adding this dataset.