Comunicació presentada a: Ninth International Conference on Language Resources and Evaluation, celebrada a Reykjavik, Iceland, del 26 al 31 de maig de 2014.

This paper empirically evaluates the performances of different state-of-the-art distributional models in a nominal lexical semantic classification task. We consider models that exploit various types of distributional features, which thereby provide different representations of nominal behavior in context. The experiments presented in this work demonstrate the advantages and disadvantages of each model considered. This analysis also considers a combined strategy that we found to be capable of leveraging the bottlenecks of each model, especially when large robust data is not available.

This work was funded with the support of the SUR of the DEC of the Generalitat de Catalunya and the European Social Fund, by SKATER TIN2012-38584-C06-05 and the EBES-IULA/UPF mobility grant, as well as the PRIN grant 20105B3HE8 ”Word Combinations in Italian: theoretical and descriptive analysis, computational models, lexicographic layout and creation of a dictionary”, funded by the Italian Ministry of Education, University and Research.