README.md

metadata

dataset_info:
  features:
    - name: q_id
      dtype: int64
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: q_word
      dtype: string
    - name: q_topic
      dtype: string
    - name: fine_class
      dtype: string
    - name: class
      dtype: string
    - name: ontology_concept
      dtype: string
    - name: ontology_concept2
      dtype: string
    - name: source
      dtype: string
    - name: q_src_id
      dtype: int64
    - name: quetion_type
      dtype: string
    - name: chapter_name
      dtype: string
    - name: chapter_no
      dtype: int64
    - name: verse
      sequence: string
    - name: question_en
      dtype: string
    - name: answer_en
      dtype: string
    - name: q_word_en
      dtype: string
    - name: q_topic_en
      dtype: string
    - name: fine_class_en
      dtype: string
    - name: class_en
      dtype: string
    - name: ontology_concept_en
      dtype: string
    - name: chapter_name_en
      dtype: string
    - name: context
      dtype: string
  splits:
    - name: train
      num_bytes: 2226830.0310711367
      num_examples: 978
    - name: test
      num_bytes: 557845.9689288634
      num_examples: 245
  download_size: 1515128
  dataset_size: 2784676
license: cc-by-4.0
task_categories:
  - question-answering
pretty_name: Quran Question Answer with Context
language:
  - ar
  - en
tags:
  - islam
  - quran
  - arabic

Dataset Card for "quran-question-answer-context"

Dataset Summary

Translated the original dataset from Arabic to English and added the Surah ayahs to the context column.

Usage

from datasets import load_dataset

dataset = load_dataset("nazimali/quran-question-answer-context")

DatasetDict({
    train: Dataset({
        features: ['q_id', 'question', 'answer', 'q_word', 'q_topic', 'fine_class', 'class', 'ontology_concept', 'ontology_concept2', 'source', 'q_src_id', 'quetion_type', 'chapter_name', 'chapter_no', 'verse', 'question_en', 'answer_en', 'q_word_en', 'q_topic_en', 'fine_class_en', 'class_en', 'ontology_concept_en', 'chapter_name_en', 'context'],
        num_rows: 978
    })
    test: Dataset({
        features: ['q_id', 'question', 'answer', 'q_word', 'q_topic', 'fine_class', 'class', 'ontology_concept', 'ontology_concept2', 'source', 'q_src_id', 'quetion_type', 'chapter_name', 'chapter_no', 'verse', 'question_en', 'answer_en', 'q_word_en', 'q_topic_en', 'fine_class_en', 'class_en', 'ontology_concept_en', 'chapter_name_en', 'context'],
        num_rows: 245
    })
})

Translation Info

1. Translated the Arabic questions/concept columns to English with Helsinki-NLP/opus-mt-ar-en
2. Used en-yusufali translations for ayas M-AI-C/quran-en-tafssirs
3. Renamed Surahs with kheder/quran
4. Added the ayahs that helped answer the questions

• Split the ayah columns string into a list of integers
• Concactenated the Surah:Ayah pairs into a sentence to the context column

Columns with the suffix _en contain the translations of the original columns.

TODO

The context column has some null values that needs to be investigated and fixed

Initial Data Collection

The original dataset is from Annotated Corpus of Arabic Al-Quran Question and Answer

Licensing Information

Original dataset license: Creative Commons Attribution 4.0 International (CC BY 4.0)

Contributions

Original paper authors: Alqahtani, Mohammad and Atwell, Eric (2018) Annotated Corpus of Arabic Al-Quran Question and Answer. University of Leeds. https://doi.org/10.5518/356