Finally, the work that most resembles ours is that of<cite> Fagarasan et al. (2015)</cite> , who use Partial Least Squares Regression (PLSR) to learn a mapping from a word embedding model onto specific conceptual properties. Concurrent work recently undertaken by Li and Summers-Stay (2019) replaces the PLSR model with a feedforward neural network. In our work, we instead map property knowledge directly into vector space models of word meaning, rather than learning a supervised predictive function from concept embedding dimensions to feature terms.