Publications
A New Concept of Knowledge based Question Answering (KBQA) System using Multiple Reasoning Paths
Published
North American Chapter of the Association for Computational Linguistics (NAACL)
Date
2022.07.10
Research Areas
Abstract
Multi-hop knowledge based question answering (KBQA) is a complex task for natural language understanding. Many KBQA approaches have been proposed in recent years, and most of them are trained based on labeled
reasoning path. This hinders the system’s performance as many correct reasoning paths are not labeled as ground truth, and thus they cannot be learned. In this paper, we introduce an end-to-end KBQA system which
can leverage multiple reasoning paths’ information and only requires labeled answer as supervision.We conduct experiments on several benchmark datasets containing both singlehop simple questions as well as muti-hop complex questions, including WebQuestionSP (WQSP), ComplexWebQuestion-1.1 (CWQ), and PathQuestion-Large (PQL), and demonstrate strong performance.
reasoning path. This hinders the system’s performance as many correct reasoning paths are not labeled as ground truth, and thus they cannot be learned. In this paper, we introduce an end-to-end KBQA system which
can leverage multiple reasoning paths’ information and only requires labeled answer as supervision.We conduct experiments on several benchmark datasets containing both singlehop simple questions as well as muti-hop complex questions, including WebQuestionSP (WQSP), ComplexWebQuestion-1.1 (CWQ), and PathQuestion-Large (PQL), and demonstrate strong performance.