PersianMHQA: A Dataset for Open Domain Persian Multi-hop Question Answering Based on Wikipedia Encyclopedia

Today, one of the most important tasks in natural language processing is answering user questions. Especially, users' questions nowadays moved from simple questions to complex questions. In recent years, several question answering datasets have been produced for Persian language, but none of them support complex open-domain and explainable questions. In this article, the PersianMHQA dataset is introduced which is the first open-domain question answering dataset for complex questions based on the unstructured Persian Wikipedia encyclopedia. This dataset contains 7,000 complex questions and sentence-level supporting facts are provided for each question that allows question answering systems to explain the predictions. The questions in this dataset are diverse and explainable and are not limited to any previous knowledge base. Various types of complexity are provided in this dataset, and the questions are designed in such a way that answering them requires reasoning over more than one paragraph.