  In distributional semantic accounts of the meaning of noun-noun compounds
(e.g. starfish, bank account, houseboat) the important role of constituent
polysemy remains largely unaddressed(cf. the meaning of star in starfish vs.
star cluster vs. star athlete). Instead of semantic vectors that average over
the different meanings of a constituent, disambiguated vectors of the
constituents would be needed in order to see what these more specific
constituent meanings contribute to the meaning of the compound as a whole. This
paper presents a novel approach to this specific problem of word sense
disambiguation: set expansion. We build on the approach developed by Mahabal et
al. (2018) which was originally designed to solve the analogy problem. We
modified their method in such a way that it can address the problem of sense
disambiguation of compound constituents. The results of experiments with a data
set of almost 9000 compounds (LADEC, Gagn\'e et al. 2019) suggest that this
approach is successful, yet the success is sensitive to the frequency with
which the compounds are attested.
