Datasets:

Sub-tasks:
fact-checking
Languages:
Arabic
ArXiv:
License:

The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

Dataset Card for AraStance

Dataset Summary

The dataset is a collection of news titles in arabic along with paraphrased and corrupted titles. The stance prediction version is a 3-class classification task. Data contains three columns: s1, s2, stance.

Languages

Arabic

Dataset Structure

Data Instances

An example of 'train' looks as follows:

{
  'id': '0', 
  's1': 'هجوم صاروخي يستهدف مطار في طرابلس ويجبر ليبيا على تغيير مسار الرحلات الجوية', 
  's2': 'هدوء الاشتباكات فى طرابلس', 
  'stance': 0
}

Data Fields

  • id: a 'string' feature.
  • s1: a 'string' expressing a claim/topic.
  • s2: a 'string' to be classified for its stance to the source.
  • stance: a class label representing the stance the article expresses towards the claim. Full tagset with indices:
                0: "disagree",
                1: "agree",
                2: "other",

Data Splits

name instances
train 2652
validation 755
test 379

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

The dataset is curated by the paper's authors

Licensing Information

The authors distribute this data under the Apache License, Version 2.0

Citation Information

@inproceedings{,
    title = "Stance Prediction and Claim Verification: An {A}rabic Perspective", 
    author = "Khouja, Jude",
    booktitle = "Proceedings of the Third Workshop on Fact Extraction and {VER}ification ({FEVER})",
    year = "2020",
    address = "Seattle, USA",
    publisher = "Association for Computational Linguistics",
}

Contributions

Thanks to mkonxd for adding this dataset.

Downloads last month
154