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extractive-qa
Languages:
Persian
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metadata
annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
languages:
  - fa
licenses:
  - cc-by-nc-sa-4-0
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - extended|wikipedia|google
task_categories:
  - question-answering
task_ids:
  - extractive-qa

Dataset Card for PersiNLU (Reading Comprehension)

Table of Contents

Dataset Description

Dataset Summary

A Persian reading comprehenion task (generating an answer, given a question and a context paragraph). The questions are mined using Google auto-complete, their answers and the corresponding evidence documents are manually annotated by native speakers.

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:

{
    'question': 'پیامبر در چه سالی به پیامبری رسید؟', 
    'url': 'https://fa.wikipedia.org/wiki/%D9%85%D8%AD%D9%85%D8%AF', 
    'passage': 'محمد که از روش زندگی مردم مکه ناخشنود بود، گهگاه در غار حرا در یکی از کوه\u200cهای اطراف آن دیار به تفکر و عبادت می\u200cپرداخت. به باور مسلمانان، محمد در همین مکان و در حدود ۴۰ سالگی از طرف خدا به پیامبری برگزیده، و وحی بر او فروفرستاده شد. در نظر آنان، دعوت محمد همانند دعوت دیگر پیامبرانِ کیش یکتاپرستی مبنی بر این بود که خداوند (الله) یکتاست و تسلیم شدن برابر خدا راه رسیدن به اوست.', 
    'answers': [
        {'answer_start': 160, 'answer_text': 'حدود ۴۰ سالگی'}
     ]
}

Data Fields

  • question: the question, mined using Google auto-complete.
  • passage: the passage that contains the answer.
  • url: the url from which the passage was mined.
  • answers: a list of answers, containing the string and the index of the answer with the fields answer_start and answer_text. Note that in the test set, some answer_start values are missing and replaced with -1

Data Splits

The train/test split contains 600/575 samples.

Dataset Creation

Curation Rationale

The question were collected via Google auto-complete. The answers were annotated by native speakers. For more 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.