Improving the Interpretation of Noun Phrases with Cross-linguistic Information
نویسنده
چکیده
This paper addresses the automatic classification of semantic relations in noun phrases based on cross-linguistic evidence from a set of five Romance languages. A set of novel semantic and contextual English– Romance NP features is derived based on empirical observations on the distribution of the syntax and meaning of noun phrases on two corpora of different genre (Europarl and CLUVI). The features were employed in a Support Vector Machines algorithm which achieved an accuracy of 77.9% (Europarl) and 74.31% (CLUVI), an improvement compared with two state-of-the-art models reported in the literature.
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تاریخ انتشار 2007