  An important challenge for the automatic analysis of English written text is
the abundance of noun compounds: sequences of nouns acting as a single noun. In
our view, their semantics is best characterized by the set of all possible
paraphrasing verbs, with associated weights, e.g., malaria mosquito is carry
(23), spread (16), cause (12), transmit (9), etc. Using Amazon's Mechanical
Turk, we collect paraphrasing verbs for 250 noun-noun compounds previously
proposed in the linguistic literature, thus creating a valuable resource for
noun compound interpretation. Using these verbs, we further construct a dataset
of pairs of sentences representing a special kind of textual entailment task,
where a binary decision is to be made about whether an expression involving a
verb and two nouns can be transformed into a noun compound, while preserving
the sentence meaning.
