CCG Categories for Distributional Semantic Models
Paramita Mirza, Raffaella Bernardi · 2013
For the last decade, distributional seman-tics has been an active area of research to address the problem of understanding the semantics of words in natural language. The core principal of the distributional se-mantic approach is that the linguistic con-text surrounding a given word, which is represented as a vector, provides important information about its meaning. In this pa-per we investigate the possibility to exploit Combinatory Categorial Grammar (CCG) categories as syntactic features to be rele-vant for characterizing the context vector and hence the meaning of words. We find that the CCG categories can enhance the representation of verb meaning. 1