Research Data Leeds Repository

Citation

Alqahtani, Mohammad and Atwell, Eric (2018) Annotated Corpus of Arabic Al-Quran Question and Answer. University of Leeds. [Dataset] https://doi.org/10.5518/356¹

Dataset description

AQQAC is a collection of approximately 2224 questions and answers about Al-Al-Quran. Each question and answer is annotated with the question ID, question word (particles), chapter number, verse number, question topic, question type, Al-Quran ontology concepts (Alqahtani & Atwell, 2018) and question source. The aim of this corpus is to provide a Question-Answering taxonomy for questions about Al-Quran. Additionally, this corpus might be used as a data set for testing and evaluating Islamic IR systems. The text of Al-Quran questions and answers were extracted from trusted two islamic sources: (1000 Su'al Wa Jawab Fi ALKORAN) was compiled by the famous Islamic scholar Ashur (2001). This book contains 1000 questions and answers about Al-Quran written in the Arabic language. Islam – Al-Quran and Tafseer is a website about Al-Quran that includes a description and a translation of Al-Quran and the reciting rules, the “Tajweed”. Additionally, this website has approximately 1224 questions and answers about Al-Quran in the Arabic language extracted from the Altabari Tafseer. Currently, this dataset contains 1224 annotated question-answers and the missing data that hasn’t been shared is due to copyright concerns.

Keywords:	quran, Q&A, corpus, NLP
Subjects:	I000 - Computer sciences > I400 - Artificial intelligence2
Divisions:	Faculty of Engineering and Physical Sciences > School of Computing3
Related resources:	Location Type https://etheses.whiterose.ac.uk/24184/4 Ethesis
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	03 Dec 2018 16:08
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/4645
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Alqahtani, Mohammad https://orcid.org/0000-0001-9403-12866 University of Leeds https://ror.org/024mrxd33 ror Jeddah University https://ror.org/015ya8798 ror Atwell, Eric https://orcid.org/0000-0001-9395-37647 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: University of Jeddah Publication date: 2018 Resource language: Arabic Metadata language: English Publisher: University of Leeds Contact email: scmmal@leeds.ac.uk8 Last Modified: 29 Jul 2024 14:55

Files

Data

Annotated Arabic Question-Answer corpus [1MB] 9 Annotated Arabic Question-Answer corpus [1MB] 10 Annotated Arabic Question-Answer corpus [1MB] 11 Security: Anyone File name: AAQQAC.XML12 Content type: Data Description: annotated text in xml format Mime-Type: text/xml License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 1MB

Annotated Arabic Question-Answer corpus [616kB] 13 Annotated Arabic Question-Answer corpus [616kB] 14 Annotated Arabic Question-Answer corpus [616kB] 15 Security: Anyone File name: AAQQAC.xlsx16 Content type: Data Description: annotated text Mime-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 616kB