This work introduces SYMPAThy, a data representation model in which the combinatorial properties of a lexical item are described by merging surface and deeper linguistic information. The proposed approach is then evaluated by comparing, for a sample list of verbal idioms, a set of SYMPAThy-based fixedness indexes against the relevant speaker-elicited indexes available in the descriptive norms collected by Tabossi et al. (2011)