  Recent work on compositional distributional models shows that bialgebras over
finite dimensional vector spaces can be applied to treat generalised
quantifiers for natural language. That technique requires one to construct the
vector space over powersets, and therefore is computationally costly. In this
paper, we overcome this problem by considering fuzzy versions of quantifiers
along the lines of Zadeh, within the category of many valued relations. We show
that this category is a concrete instantiation of the compositional
distributional model. We show that the semantics obtained in this model is
equivalent to the semantics of the fuzzy quantifiers of Zadeh. As a result, we
are now able to treat fuzzy quantification without requiring a powerset
construction.
