Qur'an QA 2023 Shared Task: Overview of Passage Retrieval and Reading Comprehension Tasks over the Holy Qur'an
| Author | Malhas, Rana |
| Author | Mansour, Watheq |
| Author | Elsayed, Tamer |
| Available date | 2024-11-05T06:05:19Z |
| Publication Date | 2023 |
| Publication Name | ArabicNLP 2023 - 1st Arabic Natural Language Processing Conference, Proceedings |
| Resource | Scopus |
| Identifier | http://dx.doi.org/10.18653/v1/2023.arabicnlp-1.76 |
| Abstract | Motivated by the need for intelligent question answering (QA) systems on the Holy Qur'an and the success of the first Qur'an Question Answering shared task (Qur'an QA 2022 at OSACT 2022), we have organized the second version at ArabicNLP 2023. The Qur'an QA 2023 is composed of two sub-tasks: the passage retrieval (PR) task and the machine reading comprehension (MRC) task. The main aim of the shared task is to encourage state-of-the-art research on Arabic PR and MRC on the Holy Qur'an. Our shared task has attracted 9 teams to submit 22 runs for the PR task, and 6 teams to submit 17 runs for the MRC task. In this paper, we present an overview of the task and provide an outline of the approaches employed by the participating teams in both sub-tasks. |
| Sponsor | We would like to thank all the Qur'an specialists who contributed to extracting/annotating the verse-based and span-based answers to the additional test questions in the datasets; especially Dr. Ahmad Shukri, Professor of Tafseer and Qur'anic Sciences at Qatar University, for his scholarly advice throughout the annotation process of the answers extracted from the Holy Qur'an. |
| Language | en |
| Publisher | Association for Computational Linguistics (ACL) |
| Subject | Computational linguistics Art research Comprehension tasks Intelligent question answering systems Participating teams Passage retrieval Question Answering Reading comprehension State of the art Subtask Natural language processing systems |
| Type | Conference |
| Pagination | 690-701 |
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