A Query Graph Generation Method for Knowledge Base Question Answering
We propose a new query graph generation method for question parsing in knowledge base question answer-ing system.With a limited coverage of complex questions,existing query graph generation methods fail in handling questions whose answers or constrains are relations or the combination or operation between path results.We employ relation-based actions as well as node-based actions during query graph generation stage,and take the com-bination of different main paths into consideration.Based on this method,we build a Chinese knowledge base ques-tion answering system.We also build a dataset of Chinese knowledge base question answering with multiple complex questions,which is merged with CCKS2019-CKBQA as a new dataset called CCKS2019-Comp.The experimental results show that the proposed method achieves average F1 value of 73.8％and 73.3％on CCKS2019-CKBQA and CCKS2019-Comp,respectively.(data and code are available on GitHub1).
knowledge base question answeringquery graph generationdata constructionquestion answering system
万方数据
维普
