  The measurement of phrasal semantic relatedness is an important metric for
many natural language processing applications. In this paper, we present three
approaches for measuring phrasal semantics, one based on a semantic network
model, another on a distributional similarity model, and a hybrid between the
two. Our hybrid approach achieved an F-measure of 77.4% on the task of
evaluating the semantic similarity of words and compositional phrases.
