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International Conference on Intelligent Text Processing and Computational Linguistics

CICLing 2003: Computational Linguistics and Intelligent Text Processing pp 158–167Cite as

Performance Analysis of a Part of Speech Tagging Task

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2588))

Abstract

In this paper, we attempt to make a formal analysis of the performance in automatic part of speech tagging. Lower and upper bounds in tagging precision using existing taggers or their combination are provided. Since we show that with existing taggers, automatic perfect tagging is not possible, we offer two solutions for applications requiring very high precision: (1) a solution involving minimum human intervention for a precision of over 98.7%, and (2) a combination of taggers using a memory based learning algorithm that succeeds in reducing the error rate with 11.6% with respect to the best tagger involved.

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Author information

Authors and Affiliations

  1. Computer Science Department, University of North Texas, 76203-1366, Denton, TX

    Rada Mihalcea

Authors
  1. Rada Mihalcea
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Editor information

Editors and Affiliations

  1. Centro de Investigación en Computación (CIC), Instituto Politécnico Nacional (IPN), Col. Zacatenco, CP 07738, Mexico D.F., Mexico

    Alexander Gelbukh

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© 2003 Springer-Verlag Berlin Heidelberg

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Mihalcea, R. (2003). Performance Analysis of a Part of Speech Tagging Task. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2003. Lecture Notes in Computer Science, vol 2588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36456-0_16

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  • DOI: https://doi.org/10.1007/3-540-36456-0_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00532-2

  • Online ISBN: 978-3-540-36456-6

  • eBook Packages: Springer Book Archive

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