We think that these are especially important experiments, because they show how the same matrix that has been used for tasks that were entirely bound to lexical items can also be used to generalize to structures that go beyond what is directly observed in the corpus.
we model here selectional preferences (how plausible a noun is as subject/object of a verb), but our method is generalizable to many other semantic tasks that pertain to composition constraints; that is, they require measuring the goodness of fit of a word/concept as argument filler of another word/concept, including assigning semantic roles, logical metonymy, coercion (Pustejovsky 1995), and many other challenges.