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Text
Languages:
Persian
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Fix `license` metadata (#1)
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metadata
annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
language:
  - fa
license:
  - cc-by-nc-sa-4.0
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - extended|quora|google
task_categories:
  - query-paraphrasing
task_ids:
  - query-paraphrasing

Dataset Card for PersiNLU (Query Paraphrasing)

Table of Contents

Dataset Description

Dataset Summary

A Persian query paraphrasng task (deciding whether two questions are paraphrases of each other). The questions are partially generated from Google auto-complete, and partially translated from the Quora paraphrasing dataset.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The text dataset is in Persian (fa).

Dataset Structure

Data Instances

Here is an example from the dataset:

{
  "q1": "اعمال حج تمتع از چه روزی شروع میشود؟",
  "q2": "ویار از چه روزی شروع میشود؟",
  "label": "0",
  "category": "natural"
}

Data Fields

  • q1: the first question.
  • q2: the second question.
  • category: whether the questions are mined from Quora (qqp) or they're extracted from Google auto-complete (natural).
  • label: 1 if the questions are paraphrases; 0 otherwise.

Data Splits

The train/dev/test splits contains 1830/898/1916 samples.

Dataset Creation

Curation Rationale

For details, check the corresponding draft.

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

CC BY-NC-SA 4.0 License

Citation Information

@article{huggingface:dataset,
    title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
    authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others},
    year={2020}
    journal = {arXiv e-prints},
    eprint = {2012.06154},    
}

Contributions

Thanks to @danyaljj for adding this dataset.