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International Conference on Text, Speech and Dialogue

TSD 2012: Text, Speech and Dialogue pp 240–247Cite as

Assigning Deep Lexical Types

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7499))

Abstract

Deep linguistic grammars provide complex grammatical representations of sentences, capturing, for instance, long-distance dependencies and returning semantic representations, making them suitable for advanced natural language processing. However, they lack robustness in that they do not gracefully handle words missing from the lexicon of the grammar. Several approaches have been taken to handle this problem, one of which consists in pre-annotating the input to the grammar with shallow processing machine-learning tools. This is usually done to speed-up parsing (supertagging) but it can also be used as a way of handling unknown words in the input. These pre-processing tools, however, must be able to cope with the vast tagset required by a deep grammar. We investigate the training and evaluation of several supertaggers for a deep linguistic processing grammar and report on it in this paper.

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Authors and Affiliations

  1. Departamento de Informática, Edifício C6, Faculdade de Ciências, University of Lisbon, Campo Grande, 1749-016, Lisboa, Portugal

    João Silva & António Branco

Authors
  1. João Silva
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  2. António Branco
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Editor information

Editors and Affiliations

  1. Faculty of Informatics, Department of Computer Graphics and Design, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Petr Sojka

  2. Faculty of Informatics, Department of Information Technologies, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Aleš Horák , Ivan Kopeček  & Karel Pala ,  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Silva, J., Branco, A. (2012). Assigning Deep Lexical Types. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_29

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  • DOI: https://doi.org/10.1007/978-3-642-32790-2_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32789-6

  • Online ISBN: 978-3-642-32790-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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