Open domain question answering system based on knowledge base

Abstract

Aiming at the task of open domain question answering based on knowledge base in NLP&CC 2016, we propose a SPE (subject predicate extraction) algorithm which can automatically extract a subject-predicate pair from a simple question and translate it to a KB query. A novel method based on word vector similarity and predicate attention is used to score the candidate predicate after a simple topic entity linking method. Our approach achieved the F1-score of 82.47% on test data which obtained the first place in the contest of NLP&CC 2016 Shared Task 2 (KBQA sub-task). Furthermore, there are also a series of experiments and comprehensive error analysis which can show the properties and defects of the new data set.