Distributional models, which describe the meaning of a word in terms of its observed contexts (Turney and Pantel, 2010), have been suggested as a model for how humans learn word meanings (Landauer and Dumais, 1997).
distributional models typically need hundreds of instances of a word to derive a highquality representation for it, while humans can often infer a passable meaning approximation from one sentence only (as in the above example).