README.md

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|translated|mnli
task_categories:
  - sentiment-analysis
task_ids:
  - sentiment-analysis

Dataset Card for PersiNLU (Textual Entailment)

Table of Contents

• Dataset Card for PersiNLU (Sentiment Analysis)
  • Table of Contents
  • Dataset Description
    • Dataset Summary
    • Supported Tasks and Leaderboards
    • Languages
  • Dataset Structure
    • Data Instances
    • Data Fields
    • Data Splits
  • Dataset Creation
    • Curation Rationale
    • Source Data
      • Initial Data Collection and Normalization
      • Who are the source language producers?
    • Annotations
      • Annotation process
      • Who are the annotators?
    • Personal and Sensitive Information
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
  • Additional Information
    • Dataset Curators
    • Licensing Information
    • Citation Information
    • Contributions

Dataset Description

• Homepage: Github
• Repository: Github
• Paper: Arxiv
• Leaderboard:
• Point of Contact: d.khashabi@gmail.com

Dataset Summary

A Persian sentiment analysis 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:

{
  "review": "خوب بود ولی خیلی گرون شده دیگه...فک نکنم به این قیمت ارزش خرید داشته باشد",
  "review_id": "1538",
  "example_id": "4",
  "excel_id": "food_194",
  "question": "نظر شما در مورد بسته بندی و نگهداری این حلوا شکری، ارده و کنجد چیست؟",
  "category": "حلوا شکری، ارده و کنجد",
  "aspect": "بسته بندی",
  "label": "-3",
  "guid": "food-dev-r1538-e4"
}

Data Fields

• review: the review text.
• review_id: a unique id associated with the review.
• example_id: a unique id associated with a particular attribute being addressed about the review.
• question: a natural language question about a particular attribute.
• category: the subject discussed in the review.
• aspect: the aspect mentioned in the input question.
• label: the overall sentiment towards this particular subject, in the context of the mentioned aspect. Here are the definition of the labels:

    '-3': 'no sentiment expressed',
    '-2': 'very negative',
    '-1': 'negative',
    '0': 'neutral',
    '1': 'positive',
    '2': 'very positive',
    '3': 'mixed',

Data Splits

See the data.

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.