Ontology-guided Extraction of Complex Nested Relationships

Many applications call for methods to enable automatic extraction of structured information from unstructured natural language text. Due to inherent challenges of natural language processing, most of the existing methods for information extraction from text tend to be domain specific. We explore a modular ontology-based approach to information extraction that decouples domain-specific knowledge from the rules used for information extraction. We describe a framework for extraction of a subset of complex nested relationships (e.g., Joe reports that Jim is a reliable employee). The extracted relationships are output in the form of sets of RDF (resource description framework) triples, which can be queried using query languages for RDF and mined for knowledge acquisition.