They are motivated by the observation that semantically similar words occur in similar contexts, so words can be represented as vectors in high dimensional spaces generated from the contexts in which they occur (Lund and Burgess 1996;Landauer and Dumais 1997).
distributional models are relatively easier to build than logical representations, automatically acquire knowledge from "big data," and capture the graded nature of linguistic meaning, but they do not adequately capture logical structure (Grefenstette 2013).