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Answering Multiple-Choice Questions in Geographical Gaokao with a Concept Graph

  • Jiwei Ding
  • Yuan Wang
  • Wei Hu
  • Linfeng Shi
  • Yuzhong Qu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10843)

Abstract

Answering questions in Gaokao (the national college entrance examination in China) brings a great challenge for recent AI systems, where the difficulty of questions and the lack of formal knowledge are two main obstacles, among others. In this paper, we focus on answering multiple-choice questions in geographical Gaokao. Specifically, a concept graph is automatically constructed from textbook tables and Chinese wiki encyclopedia, to capture core concepts and relations in geography. Based on this concept graph, a graph search based question answering approach is designed to find explainable inference paths between questions and options. We developed an online system called CGQA and conducted experiments on two real datasets created from the last ten year geographical Gaokao. Our experimental results demonstrated that CGQA can generate accurate judgments and provide explainable solving procedures. Additionally, CGQA showed promising improvement by combining with existing approaches.

Keywords

Concept graph Geographical Gaokao Question answering CGQA 

Notes

Acknowledgments

This work is funded by the National Natural Science Foundation of China (No. 61772264) and the National High-tech R&D Program of China (No. 2015AA015406). We thank all participants in the evaluation for their time and effort.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.National Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingChina

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