基于层次化语义框架的知识库属性映射方法

面向知识库的自动问答是自然语言处理的一项重要任务,其旨在对用户提出的自然语言形式问题给出精练、准确的回复.目前由于缺少数据集,存在特征不一致等因素,导致难以使用通用的数据和方法实现领域知识库问答.因此,该文将"问题意图"视作不同领域问答可能存在的共同特征,将"问题"与三元组知识库中"关系谓词"的映射过程作为问答核心工作...

Property Mapping in Knowledge Base Under the Hierarchical Semantic Framework

Knowledge Base Question Answer (KBQA) is a natural language processing task to generate refined and accurate responses to natural language questions raised by users. Therefore, this paper treats the question intent identification as the common issue for KBQA of various domains, and the mapping between the question and the predicate of the tuple in the knowledge base as the key issue. Specifically, we combine the "gated convolution for deep semantics" and " interactive attention mechanism for shallow semantics" into a unified framework via the gated perception mechanism. Experiments on NLPCC-ICCPOL 2016 KBQA dataset show that our proposed method significantly outperforms the existing CDSSM and BDSSM. Besides, we adapt our method for a commonsense automatic question answering system via a commonsense knowledge base of astronomy.