For adjectives and verbs, we compared the initial model's (λ max ) intercept and the minimum cross-validation error model intercept with corpus-extracted vectors for the corresponding words.
we used the word cooccurrence vector for a verb or an adjective extracted from the corpus and projected onto the reduced feature space (e.g., NMF, 100 dimensions), then computed cosine similarity between this word meaning representation and its corresponding EnetLex matrix initial and minimumerror intercepts, respectively.