--- 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: 2784676.0 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 ```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