Explainable multi-hop dense question answering using knowledge bases and text

Much research has been conducted extracting a response from either text sources or a knowledge base (KB). The challenge be-comes more complicated when the goal is to answer a question with the help of both text and KB. In these hybrid systems, we address the following challenges: i) excessive growth of search space, ii) extraction of the answer from both KB and text, iii) extracting the path to reach to the answer. A heterogeneous graph is utilized to tackle the first challenge guided by question de-composition. The second challenge is met with the usage of the idea behind an existing text-based method, and its customization for graph development. Based on this method for multi-hop questions, an approach is proposed for the extraction of answer ex-planation to address the third challenge. Evaluation reveals that the proposed method has the ability to extract answers in an ac-ceptable time, while offering competitive accuracy and has created a trade-off between performance and accuracy in comparison with the base methods.