Towards An Automatic Verb Classification For Spanish: Study Of The Relevance Of Different Types And Configurations Of Syntactico-Semantic Information

In this work we focus on the automatic acquisition of verbal classifications for Spanish. To do so, we perform a series of experiments with 20 verbal senses that belong to the Sensem corpus. We use different kinds of features that include diverse linguistic information and an agglomerative hierarchical clustering method to generate a number of classifications. We compare each of these automatic classifications with a semi-automatically created gold standard, which is built on the basis of linguistic constructions proposed by theoretical linguistics. This comparison allows us to investigate which features are adequate to build a verb classification coherent with linguistic constructions theory and which are the similarities and differences between an automatic verbal classification and a verb classification based on the theory of linguistic constructions.