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Learning to Interpret Novel Noun-Noun Compounds: Evidence from Category Learning Experiments

  • Barry J. Devereux
  • Fintan J. Costello
Chapter
Part of the Theory and Applications of Natural Language Processing book series (NLP)

Abstract

The ability to correctly learn to interpret and produce novel noun-noun compounds such as wind farm or carbon tax is an important part of the acquisition of language in various domains of discourse. One approach to the interpretation of noun-noun compounds assumes that people make use of distributional information about the linguistic behaviour of words and how they tend to combine in noun-noun phrases; another assumes that people activate and integrate information about the two constituent concepts’ features to produce interpretations. We present a series of experiments that examine how people acquire both the distributional information and conceptual information that is relevant to compound interpretation. We propose that the relations used to link the two words in noun-noun compounds have rich semantic structure, which includes information about what features of concepts are necessary and/or characteristic for particular relations, as well as distributional information about the frequency with which relations co-occur with different concepts. We present an exemplar-based model of the semantics of relations which captures both of these aspects of relation meaning, and show how it can predict experimental participants’ interpretations of novel noun-noun compounds.

Keywords

Relation Selection Head Noun Relation Likelihood Training Item Plant Category 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This research was funded by Irish Research Council for Science, Engineering and Technology Grant RS/2002/758-2 to BD.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Centre for Speech, Language and the Brain, Department of PsychologyUniversity of CambridgeCambridgeUK
  2. 2.School of Computer Science and InformaticsUniversity College DublinDublinIreland

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