README.md

metadata

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: 5095721
      num_examples: 258240
  download_size: 17063406
  dataset_size: 5095721

Dataset Card for CANER

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

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 sample
• token: the tokens of the example text
• ner_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.