Discourse Topics and Metaphors

by Beata Beigman Klebanov , Eyal Beigman , Daniel Diermeier

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Datum	Value	Source
TITLE	Discourse Topics and Metaphors	SVM HeaderParse 0.2
AUTHOR NAME	Beata Beigman Klebanov	SVM HeaderParse 0.2
AUTHOR AFFIL	Northwestern University	SVM HeaderParse 0.2
AUTHOR NAME	Eyal Beigman	SVM HeaderParse 0.2
AUTHOR AFFIL	Washington University in St. Louis	SVM HeaderParse 0.2
AUTHOR NAME	Daniel Diermeier	SVM HeaderParse 0.2
AUTHOR AFFIL	Northwestern University	SVM HeaderParse 0.2
ABSTRACT	Using metaphor-annotated material that is sufficiently representative of the topical composition of a similar-length document in a large background corpus, we show that words expressing a discourse-wide topic of discussion are less likely to be metaphorical than other words in a document. Our results suggest that to harvest metaphors more effectively, one is advised to consider words that do not represent a discourse topic. Traditionally, metaphor detectors use the observation that a metaphorically used item creates a local incongruity because there is a violation of a selectional restriction, such as providing a non-vehicle object to the verb derail in Protesters derailed the conference. Current state of art in metaphor detection therefore tends to be “localistic ” – the distributional profile of the target word in its immediate grammatical or collocational context in a background corpus or a database like WordNet is used to determine metaphoricity	SVM HeaderParse 0.2
CITATIONS	14 found	ParsCit 1.0