Motivated by the resurgence of the machine reading comprehension (MRC) research, we have organized the first Qur’an Question Answering shared task, “Qur’an QA 2022”. The task in its first year aims to promote state-of-the-art research on Arabic QA in general and MRC in particular on the Holy Qur’an, which constitutes a rich and fertile source of knowledge for Muslim and non-Muslim inquisitors and knowledge-seekers. In this paper, we provide an overview of the shared task that succeeded in attracting 13 teams to participate in the final phase, with a total of 30 submitted runs. Moreover, we outline the main approaches adopted by the participating teams in the context of highlighting some of our perceptions and general trends that characterize the participating systems and their submitted runs.

We introduce AraFacts, the first large Arabic dataset of naturally occurring claims collected from 5 Arabic fact-checking websites, e.g., Fatabyyano and Misbar, and covering claims since 2016. Our dataset consists of 6,121 claims along with their factual labels and additional metadata, such as fact-checking article content, topical category, and links to posts or Web pages spreading the claim. Since the data is obtained from various fact-checking websites, we standardize the original claim labels to provide a unified label rating for all claims. Moreover, we provide revealing dataset statistics and motivate its use by suggesting possible research applications. The dataset is made publicly available for the research community.