Identifying non-compositional idioms in text using WordNet synsets. Baron, F. Master's thesis, Department of Computer Science, University of Toronto, 2007.
abstract   bibtex   

Any natural language processing system that does not have a knowledge of non-compositional idioms and their interpretation will make mistakes. Previous authors have attempted to automatically identify these expressions through the property of non-substitutability: similar words cannot be successfully substituted for words in non-compositional idiom expressions without changing their meaning.

In this study, we use the non-substitutability property of idioms to contrast and expand the ideas of previous works, drawing on WordNet for the attempted substitutions. We attempt to determine the best way to automatically identify idioms through the comparison of algorithms including frequency counts, pointwise mutual information and PMI ranges; the evaluation of the importance of relative word position; and the assessment of the usefulness of syntactic relations. We discover that many of the techniques which we try are not useful for identifying idioms and confirm that non-compositionality doesn't appear to be a necessary or sufficient condition for idiomaticity.

@MastersThesis{	  baron2,
  author	= {Faye Baron},
  title		= {{Identifying non-compositional idioms in text using
		  WordNet synsets}},
  year		= {2007},
  school	= {Department of Computer Science, University of Toronto},
  abstract	= {<p>Any natural language processing system that does not
		  have a knowledge of non-compositional idioms and their
		  interpretation will make mistakes. Previous authors have
		  attempted to automatically identify these expressions
		  through the property of non-substitutability: similar words
		  cannot be successfully substituted for words in
		  non-compositional idiom expressions without changing their
		  meaning.</p> <p>In this study, we use the
		  non-substitutability property of idioms to contrast and
		  expand the ideas of previous works, drawing on WordNet for
		  the attempted substitutions. We attempt to determine the
		  best way to automatically identify idioms through the
		  comparison of algorithms including frequency counts,
		  pointwise mutual information and PMI ranges; the evaluation
		  of the importance of relative word position; and the
		  assessment of the usefulness of syntactic relations. We
		  discover that many of the techniques which we try are not
		  useful for identifying idioms and confirm that
		  non-compositionality doesn't appear to be a necessary or
		  sufficient condition for idiomaticity. </p> },
  download	= {http://ftp.cs.toronto.edu/pub/gh/Baron-thesis.pdf}
}

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