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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.
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