Performance Analysis of a Part of Speech Tagging Task

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This article discusses performance analysis of a part of speech tagging task.

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10 p.

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Mihalcea, Rada, 1974- February 2003.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Engineering to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 850 times, with 7 in the last month. More information about this paper can be viewed below.

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This article discusses performance analysis of a part of speech tagging task.

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10 p.

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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, two solutions for applications requiring very high precision are presented: (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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  • Fourth International Conference on Intelligent Text Processing and Computational Linguists (CICLING), February 16-22, 2003. Mexico City, Mexico

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  • February 2003

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  • Jan. 31, 2011, 2:01 p.m.

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  • Nov. 30, 2023, 2:31 p.m.

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Mihalcea, Rada, 1974-. Performance Analysis of a Part of Speech Tagging Task, paper, February 2003; [Berlin, Germany]. (https://digital.library.unt.edu/ark:/67531/metadc30950/: accessed March 29, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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