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Geography Gaokao-Oriented Knowledge Acquisition for Comparative Sentences Based on Logic Programming

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Natural Language Processing and Chinese Computing (NLPCC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10619))

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Abstract

Multiple-choice questions of comparing one entity with another in a university’s entrance examination like Gaokao in China are very common but require high knowledge skill. As a preliminary attempt to address this problem, we build a geography Gaokao-oriented knowledge acquisition system for comparative sentences based on logic programming to help solve real geography examinations. Our work consists of two consecutive tasks: identify comparative sentences from geographical texts and extract comparative elements from the identified comparative sentences. Specifically, for the former task, logic programming is employed to filter out non-comparative sentences, and for the latter task, the information of dependency grammar and heuristic position is adopted to represent the relations among comparative elements. The experimental results show that our system achieves outstanding performance for practical use.

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Notes

  1. 1.

    http://w3id.org/clinga.

  2. 2.

    http://www.geonames.org/ontology.

  3. 3.

    http://www.geolink.org.

  4. 4.

    https://potassco.org/.

  5. 5.

    http://www.ltp-cloud.com/demo/.

  6. 6.

    http://baike.baidu.com.

  7. 7.

    http://www.corpora.com.cn/GaoKaoGeographyComSen/.

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Acknowledgement

This work is partially funded by the 863 Program under Grant 2015AA015406 and the National Natural Science Foundation of China under Grant 61702279, 61170165, 61602260, 61502095.

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Correspondence to Zhiqiang Gao .

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Li, X. et al. (2018). Geography Gaokao-Oriented Knowledge Acquisition for Comparative Sentences Based on Logic Programming. In: Huang, X., Jiang, J., Zhao, D., Feng, Y., Hong, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2017. Lecture Notes in Computer Science(), vol 10619. Springer, Cham. https://doi.org/10.1007/978-3-319-73618-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-73618-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73617-4

  • Online ISBN: 978-3-319-73618-1

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