Semanticizing Syntactic Patterns in NLP Processing Using SPARQL-DL Queries.

Some recent works on natural language semantic parsing make use of syntax and semantics together using different combination models. In our work we attempt to use SPARQL-DL as an interface between syntactic information given by the Stanford statistical parser (namely part-of-speech tagged text and typed dependency representation) and semantic information obtained from the FrameNet database. We use SPARQL-DL queries to check the presence of syntactic patterns within a sentence and identify their role as frame elements. The choice of SPARQL-DL is due to its usage as a common reference language for semantic applications and its high expressivity, which let rules to be generalized exploiting the inference capabilities of the underlying reasoner.