GOF at Qur’an QA 2022: Towards an Efficient Question Answering For The Holy Qu’ran In The Arabic Language Using Deep Learning-Based Approach

Ali Mostafa, Omar Mohamed


Abstract
Recently, significant advancements were achieved in Question Answering (QA) systems in several languages. However, QA systems in the Arabic language require further research and improvement because of several challenges and limitations, such as a lack of resources. Especially for QA systems in the Holy Qur’an since it is in classical Arabic and most recent publications are in Modern Standard Arabic. In this research, we report our submission to the Qur’an QA 2022 Shared task-organized with the 5th Workshop on Open-Source Arabic Corpora and Processing Tools Arabic (OSACT5). We propose a method for dealing with QA issues in the Holy Qur’an using Deep Learning models. Furthermore, we address the issue of the proposed dataset’s limited sample size by fine-tuning the model several times on several large datasets before fine-tuning it on the proposed dataset achieving 66.9% pRR 54.59% pRR on the development and test sets, respectively.
Anthology ID:
2022.osact-1.12
Volume:
Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Hend Al-Khalifa, Tamer Elsayed, Hamdy Mubarak, Abdulmohsen Al-Thubaity, Walid Magdy, Kareem Darwish
Venue:
OSACT
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
104–111
Language:
URL:
https://aclanthology.org/2022.osact-1.12
DOI:
Bibkey:
Cite (ACL):
Ali Mostafa and Omar Mohamed. 2022. GOF at Qur’an QA 2022: Towards an Efficient Question Answering For The Holy Qu’ran In The Arabic Language Using Deep Learning-Based Approach. In Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection, pages 104–111, Marseille, France. European Language Resources Association.
Cite (Informal):
GOF at Qur’an QA 2022: Towards an Efficient Question Answering For The Holy Qu’ran In The Arabic Language Using Deep Learning-Based Approach (Mostafa & Mohamed, OSACT 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.osact-1.12.pdf
Data
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