Leveraging Knowledge Graph for Open-Domain Question Answering

Abstract

Rich and comprehensive knowledge graphs (KG) of the Web, such as, Google KG, NELL, and Diffbot KG, are becoming increasingly prevalent and powerful as the underlying AI technology is rapidly progressing. In this work, we leverage this ongoing advancement for the task of answering questions posed from any domain and any type (factoid and non-factoid). We present a framework for knowledge graph based question answering systems, KGQA, and experiment with an instance of this framework that employs Diffbot KG. The unique features offered by KGs, such as, rapid query response time, connections between related graph objects, and structured information, are used to design a QA system that is effective and efficient.