Parsing mistakes impose an upper bound in performance on many information extraction systems. In particular, syntactic errors detecting appositive structures limit the system’s ability to capture class-instance relations automatically from texts. The article presents a method that considers semantic information to correct appositive structures given by a parser. First, we build automatically a background knowledge base from a reference collection, capturing evidence of semantic compatibility among classes and instances. Then, we evaluate three different probabilistic-based measures to identify the correct dependence on ambiguous appositive structures. Results reach a 91.4% of correct appositions which is a relative improvement of 12.9% with respect to the best baseline (80.9%) given by a state of the art parser. 
On improving parsing with automatically acquired semantic classes