A hybrid approach for relation extraction aimed to semantic annotations

We present an approach for relation extraction from texts aimed to enrich the semantic annotations produced by a semantic web portal. The approach exploits linguistic and empirical strategies, by means of a pipeline method involving processes such as a parser, part-of-speech tagger, named entity recognition system, pattern-based classification and word sense disambiguation models, and resources such as an ontology, knowledge base and lexical databases. With the use of knowledge intensive strategies to process the input data and corpus-based techniques to deal both with unpredicted cases and ambiguity problems, we expect to accurately discover most of the relevant relations for known and new entities, in an automated way.