  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 to
build a dictionary of meanings for English verbs using the CPA annotation
process. CPA parsing is one of the subtasks which this annotation process is
made of and it is the focus of this report. A supervised machine-learning
approach has been implemented, in which syntactic features derived from parse
trees and semantic features derived from WordNet and word embeddings are used.
It is shown that this approach performs well, even with the data sparsity
issues that characterize the dataset, and can obtain better results than other
system by a margin of about 4% f-score.
