He has been working in building models for robust syntactic parsing and for knowledge acquisition from corpora. In the last years, he worked on textual entailment recognition models where he mainly explored the application of supervised machine learning models to learn inference rules from annotated examples. He participated in the all the Pascal and the NIST Recognizing Textual Entailment challenges with two different systems that explore different models for the use of supervised learning algorithms to the Textual Entailment recognition problem.