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Corpus Pattern Analysis (CPA) has been the topic of Semeval 2015 Task 15,aimed at producing a system that can aid lexicographers in their efforts tobuild a dictionary of meanings for English verbs using the CPA annotationprocess. CPA parsing is one of the subtasks which this annotation process ismade of and it is the focus of this report. A supervised machine-learningapproach has been implemented, in which syntactic features derived from parsetrees and semantic features derived from WordNet and word embeddings are used.It is shown that this approach performs well, even with the data sparsityissues that characterize the dataset, and can obtain better results than othersystem by a margin of about 4% f-score.

Syntactic and semantic classification of verb arguments using dependency-based and rich semantic features