2016/04/19 by Francesco Elia, Elia, Francesco
Arts and Humanities · Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Sentiment Analysis and Opinion Mining #Topic Modeling #Translation Studies and Practices #cs.CL
paper · pdf · doi:10.48550/arxiv.1604.05747
arxiv created 2016/04/19 · openalex publication_date 2016/04/19 · arxiv updated 2016/04/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.