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Syntactic features and word similarity for supervised metonymy resolution Export

by: M. Nissim, K. Markert
(2003)

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We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-modifier relations are a high precision feature for metonymy recognition but suffer from data sparseness.


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