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ArabicTE / README.md
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metadata
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: Premise
      dtype: string
    - name: Hypothesis
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': ' NotEntails'
            '1': ' Entails'
  splits:
    - name: train
      num_bytes: 153939
      num_examples: 422
  download_size: 81786
  dataset_size: 153939

Dataset Card for ArabicTE

Table of Contents

Dataset Description

  • Homepage: [info]
  • Repository: [info]
  • Paper: [info]
  • Leaderboard: [info]
  • Point of Contact: [info]

Dataset Summary

[More Information Needed]

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

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

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@article{Alabbas_2013,
   title={Natural Language Inference for Arabic Using Extended Tree Edit Distance with Subtrees},
   volume={48},
   ISSN={1076-9757},
   url={http://dx.doi.org/10.1613/jair.3892},
   DOI={10.1613/jair.3892},
   journal={Journal of Artificial Intelligence Research},
   publisher={AI Access Foundation},
   author={Alabbas, M. and Ramsay, A.},
   year={2013},
   month=oct, pages={1–22} }

Contributions

Thanks to @github-username for adding this dataset.