Resolving Lexical Ambiguity inTensor Regression Models of Meaning
Table 3: Results for the phrase similarity task. The difference between the ambiguous and the disambiguated version is s.s. with p<0.001.
['[BOLD] Model', '[BOLD] Spearman’s  [ITALIC] ρ']
First of all, the regression model is based on the assumption that the holistic vectors of the exemplar verb phrases follow an ideal distributional behaviour that the model aims to approximate as close as possible. Next, observe that the prior disambiguation model approximates this behaviour very closely (0.399) on unseen data, with a difference not statistically significant. This is very important, since a regression model can only perform as well as its training dataset allows it; and in our case this is achieved to a very satisfactory level.