  Nowadays, one of the main challenges for Question Answering Systems is to
answer complex questions using various sources of information. Multi-hop
questions are a type of complex questions that require multi-step reasoning to
answer. In this article, the IslamicPCQA dataset is introduced. This is the
first Persian dataset for answering complex questions based on non-structured
information sources and consists of 12,282 question-answer pairs extracted from
9 Islamic encyclopedias. This dataset has been created inspired by the HotpotQA
English dataset approach, which was customized to suit the complexities of the
Persian language. Answering questions in this dataset requires more than one
paragraph and reasoning. The questions are not limited to any prior knowledge
base or ontology, and to provide robust reasoning ability, the dataset also
includes supporting facts and key sentences. The prepared dataset covers a wide
range of Islamic topics and aims to facilitate answering complex Persian
questions within this subject matter
