Corrección no Supervisada de Dependencias Sintácticas de Aposición mediante Clases Semánticas.

In this article we explore how automatic acquired semantic knowledge from large text collections allows to improve a syntactic parser. We propose an unsupervised method that corrects appositions dependencies by searching candidates in its context more semantically suitable than the one proposed by the syntactic parser in the first place.