A Joint Model for Question Answering over Multiple Knowledge Bases

Zhang, Yuanzhe (Institute of Automation, Chinese Academy of Sciences) | He, Shizhu (Institute of Automation, Chinese Academy of Sciences) | Liu, Kang (Institute of Automation, Chinese Academy of Sciences) | Zhao, Jun (Institute of Automation, Chinese Academy of Sciences)

AAAI Conferences 

As the amount of knowledge bases (KBs) grows rapidly, the problem of question answering (QA) over multiple KBs has drawn more attention. The most significant distinction between multiple KB-QA and single KB-QA is that the former must consider the alignments between KBs. The pipeline strategy first constructs the alignments independently, and then uses the obtained alignments to construct queries. However, alignment construction is not a trivial task, and the introduced noises would be passed on to query construction. By contrast, we notice that alignment construction and query construction are interactive steps, and jointly considering them would be beneficial. To this end, we present a novel joint model based on integer linear programming (ILP), uniting these two procedures into a uniform framework. The experimental results demonstrate that the proposed approach outperforms state-of-the-art systems, and is able to improve the performance of both alignment construction and query construction.