Using Automatic Question Generation Web Services Tools to Build a Quran Question-and-Answer Dataset

Abstract

Question-and-answer datasets are essential in many fields, including questions related to the Quran, but there is still a lack of a Quran question-and-answer corpus. Therefore, this research paper aimed to create a valuable dataset for the research community using automatic question generation models. We first reviewed all the tools as black boxes, not as computational linguistics algorithms, compared them, and explored their features and drawbacks. We then identified freely available tools, which are the Explore AI Question Generation demo, the Cathoven Question Generator, the Questgen Question Generator, and the Lumos Learning Question Generator. Lastly, we created a corpus of Quran questions and answers using these web service tools. Our experiment indicates that these tools’ performance varies in terms of many criteria, both the tools’ performance in general and in terms of specific standards that measure the quality of the generated questions and answers. The Cathoven Question Generator was found to be the best tool in terms of general performance. Using these tools, we generated 40,585 questions and answers based on the English translation of the Quran.