Linguistic Considerations in Automatic Question Generation

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This paper describes an automatic question generator that uses semantic pattern recognition to create questions of varying depth and type for self-study or tutoring.

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6 p.

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Mazidi, Karen & Nielsen, Rodney D. June 2014.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 36 times . More information about this paper can be viewed below.

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Description

This paper describes an automatic question generator that uses semantic pattern recognition to create questions of varying depth and type for self-study or tutoring.

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6 p.

Notes

Abstract: As students read expository text, comprehension is improved by pausing to answer questions that reinforce the material. We describe an automatic question generator that uses semantic pattern recognition to create questions of varying depth and type for self-study or tutoring. Throughout, we explore how linguistic considerations inform system design. In the described system, semantic role labels of source sentences are used in a domain-independent manner to generate both questions and answers related to the source sentence. Evaluation results show a 44% reduction in the error rate relative to the best prior systems, averaging over all metrics, and up to 61% reduction in the error rate on grammaticality judgments.

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  • 52nd Annual Meeting of the Association for Computational Linguistics, June 23-25, 2014. Baltimore, Maryland

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  • Publication Title: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers)
  • Pages: 321-326
  • Peer Reviewed: Yes

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  • June 2014

Added to The UNT Digital Library

  • Sept. 17, 2017, 6:24 p.m.

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Mazidi, Karen & Nielsen, Rodney D. Linguistic Considerations in Automatic Question Generation, paper, June 2014; Stroudsburg, Pennsylvania. (digital.library.unt.edu/ark:/67531/metadc993383/: accessed October 22, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.