Bootstrapping an Italian VerbNet: data-driven analysis of verb alternations
Gianluca E. Lebani, Veronica Viola, Alessandro Lenci · 2014
The goal of this paper is to propose a classification of the syntactic alternations admitted by the most frequent Italian verbs.The data-driven two-steps procedure exploited and the structure of the identified classes of alternations are presented in depth and discussed.Even if this classification has been developed with a practical application in mind, namely the semi-automatic building of a VerbNet-like lexicon for Italian verbs, partly following the methodology proposed in the context of the VerbNet project, its availability may have a positive impact on several related research topics and Natural Language Processing tasks.