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Comparative results on using inductive logic programming for corpus-based parser construction

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Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing (IJCAI 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1040))

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Abstract

This paper presents results from recent experiments with Chill, a corpus-based parser acquisition system. Chill treats language acquisition as the learning of search-control rules within a logic program. Unlike many current corpus-based approaches that use statistical learning algorithms, Chill uses techniques from inductive logic programming (ILP) to learn relational representations. Chill is a very flexible system and has been used to learn parsers that produce syntactic parse trees, case-role analyses, and executable database queries. The reported experiments compare Chill's performance to that of a more naive application of ILP to parser acquisition. The results show that ILP techniques, as employed in Chill, are a viable alternative to statistical methods and that the control-rule framework is fundamental to Chill's success.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, Drake University, 50311, Des Moines, IA, USA

    John M. Zelle

  2. Department of Computer Sciences, University of Texas, 78712, Austin, TX, USA

    Raymond J. Mooney

Authors
  1. John M. Zelle
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  2. Raymond J. Mooney
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Editor information

Stefan Wermter Ellen Riloff Gabriele Scheler

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© 1996 Springer-Verlag Berlin Heidelberg

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Zelle, J.M., Mooney, R.J. (1996). Comparative results on using inductive logic programming for corpus-based parser construction. In: Wermter, S., Riloff, E., Scheler, G. (eds) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. IJCAI 1995. Lecture Notes in Computer Science, vol 1040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60925-3_59

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  • DOI: https://doi.org/10.1007/3-540-60925-3_59

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60925-4

  • Online ISBN: 978-3-540-49738-7

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