Open Domain Question Answering using Knowledge Graph

Giho Lee, Incheol Kim

http://doi.org/10.5626/JOK.2020.47.9.853

In this paper, we propose a novel knowledge graph inference model called KGNet for answering the open domain complex questions. This model addresses the problem of knowledge base incompleteness. In this model, two different types of knowledge resources, knowledge base and corpus, are integrated into a single knowledge graph. Moreover, to derive answers to complex multi-hop questions effectively, this model adopts a new knowledge embedding and reasoning module based on Graph Neural Network (GNN). We demonstrate the effectiveness and performance of the proposed model through various experiments over two large question answering benchmark datasets, WebQuestionsSP and MetaQA.