Hierarchical Type Constrained Topic Entity Detection for Knowledge Base Question Answering

Yunqi Qiu, Manling Li, Yuanzhuo Wang, Yantao Jia, Xiaolong Jin

Abstract: Topic entity detection is to find out the main entity asked in a question, which is significant in question answering. Traditional methods ignore the information of entities, especially entity types and their hierarchical structures, restricting the performance. To take full advantage of Knowledge Base(KB) and detect topic entities correctly, we propose a deep neural model to leverage type hierarchy and relations of entities in KB. Experimental results demonstrate the effectiveness of the proposed method.