Datasets:
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---
language:
- ar
- en
license: cc-by-4.0
task_categories:
- question-answering
pretty_name: Quran Question Answer with Context
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: 2279271
num_examples: 978
- name: test
num_bytes: 505411
num_examples: 245
download_size: 1503529
dataset_size: 2784682
tags:
- islam
- quran
- arabic
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# 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
```python
from datasets import load_dataset
dataset = load_dataset("nazimali/quran-question-answer-context")
```
```python
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](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en)
2. Used `en-yusufali` translations for ayas [M-AI-C/quran-en-tafssirs](https://huggingface.co/datasets/M-AI-C/quran-en-tafssirs)
3. Renamed Surahs with [kheder/quran](https://huggingface.co/datasets/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](https://archive.researchdata.leeds.ac.uk/464/)**
## Licensing Information
Original dataset [license](https://archive.researchdata.leeds.ac.uk/464/): **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 |