  Formal and distributional semantic models offer complementary benefits in
modeling meaning. The categorical compositional distributional (DisCoCat) model
of meaning of Coecke et al. (arXiv:1003.4394v1 [cs.CL]) combines aspected of
both to provide a general framework in which meanings of words, obtained
distributionally, are composed using methods from the logical setting to form
sentence meaning. Concrete consequences of this general abstract setting and
applications to empirical data are under active study (Grefenstette et al.,
arxiv:1101.0309; Grefenstette and Sadrzadeh, arXiv:1106.4058v1 [cs.CL]). . In
this paper, we extend this study by examining transitive verbs, represented as
matrices in a DisCoCat. We discuss three ways of constructing such matrices,
and evaluate each method in a disambiguation task developed by Grefenstette and
Sadrzadeh (arXiv:1106.4058v1 [cs.CL]).
