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Assigning Function Tags with a Simple Model

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3406))

Abstract

This paper presents a method to assign function tags based on a Naive Bayes approach. The method takes as input a parse tree and labels certain constituents with a set of functional marks such as logical subject, predicate, etc. The performance reported is promising, given the simplicity of a Naive Bayes approach, when compared with similar work.

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References

  1. Blaheta, D., Johnson, M.: Assigning Function Tags to Parsed Text. In: Proceedings of the 1st Annual Meeting of the North American Chapter of the Association for Computational Linguistics, Seattle, May 2000, pp. 234–240 (2000)

    Google Scholar 

  2. Collins, M.: Three Generative, Lexicalised Models for Statistical Parsing. In: Proceedings of the Thirty-Fifth Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics

    Google Scholar 

  3. Friedman, J.: On bias, variance, 0/1 - loss, and the curse-of-dimensionality. Data Mining and Knowledge Discovery 1, 55–77 (1997)

    Article  Google Scholar 

  4. Jijkoun, V., de Rijke, M.: Enriching the Output of a Parser Using Memory-Based Learning. In: Proceedings of the ACL 2004 (2004)

    Google Scholar 

  5. Johnson, M.: A simple pattern-matching algorithm for recovering empty nodes and their antecedents. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics

    Google Scholar 

  6. McCallum, A., Nigam, K.: A Comparison of Event Models for Naive Bayes Text Classification. In: Workshop on Learning for Text Categorization. AAAI, Menlo Park (1998)

    Google Scholar 

  7. Bies, A., Ferguson, M., Katz, K., MacIntyre, R.: Bracketing Guidelines for Treebank II Style. Penn Treebank Project

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Rus, V., Desai, K. (2005). Assigning Function Tags with a Simple Model. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2005. Lecture Notes in Computer Science, vol 3406. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30586-6_10

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  • DOI: https://doi.org/10.1007/978-3-540-30586-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24523-0

  • Online ISBN: 978-3-540-30586-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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