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International Conference on Learning Language in Logic

LLL 1999: Learning Language in Logic pp 143–156Cite as

Experiments in Inductive Chart Parsing

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1925))

Abstract

We use Inductive Logic Programming (ILP) within a chartparsing framework for grammar learning. Given an existing grammar G, together with some sentences which G can not parse, we use ILP to find the “missing” grammar rules or lexical items. Our aim is to exploit the inductive capabilities of chart parsing, i.e. the ability to efficiently determine what is needed for a parse. For each unparsable sentence, we find actual edges and needed edges: those which are needed to allow a parse. The former are used as background knowledge for the ILP algorithm (PProgol) and the latter are used as examples for the ILP algorithm. We demonstrate our approach with a number of experiments using contextfree grammars and a feature grammar.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of York, Y010 5DD, Heslington, York, UK

    James Cussens

  2. University of Cambridge Computer Laboratory, New Museums Site, Pembroke Street, CB2 3QG, Cambridge, UK

    Stephen Pulman

Authors
  1. James Cussens
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  2. Stephen Pulman
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of York, YO10 5DD, Heslington, York, UK

    James Cussens

  2. Jožef Stefan Institute, Jamova 39, 1000, Ljubljana, Slovenia

    Sašo Džeroski

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© 2000 Springer-Verlag Berlin Heidelberg

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Cussens, J., Pulman, S. (2000). Experiments in Inductive Chart Parsing. In: Cussens, J., Džeroski, S. (eds) Learning Language in Logic. LLL 1999. Lecture Notes in Computer Science(), vol 1925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40030-3_9

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  • DOI: https://doi.org/10.1007/3-540-40030-3_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41145-1

  • Online ISBN: 978-3-540-40030-1

  • eBook Packages: Springer Book Archive

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