Multi-Hop Open-Domain Question Answering over Structured and Unstructured Knowledge

Abstract

Open-domain question answering systems need to answer question of our interests with structured and unstructured information. However, existing approaches only select one source to generate answer or only conduct reasoning on structured information. In this paper, we propose a Document-Entity Heterogeneous Graph Network, referred to as DEHG, to effectively integrate different sources of information, and conduct reasoning on heterogeneous information. DEHG employs a graph constructor to integrate structured and unstructured information, a context encoder to represent nodes and question, a heterogeneous information reasoning layer to conduct multi-hop reasoning on both information sources, and an answer decoder to generate answers for the question. Experimental results on HybirdQA dataset show that DEHG outperforms the state-of-the-art methods.