Semantic Matching: Formal Ontological Distinctions for Information Organization, Extraction, and Integration

The task of information extraction can be seen as a problem of semantic matching between a user-defined template and a piece of information written in natural language. To this purpose, the ontological assumptions of the template need to be suitably specified, and compared with the ontological implications of the text. So-called “ontologies”, consisting of theories of various kinds expressing the meaning of shared vocabularies, begin to be used for this task. This paper addresses the theoretical issues related to the design and use of such ontologies for purposes of information retrieval and extraction. After a discussion on the nature of semantic matching within a model-theoretical framework, we introduce the subject of Formal Ontology, showing how the notions of parthood, integrity, identity, and dependence can be of help in understanding, organizing and formalizing fundamental ontological distinctions. We present then some basic principles for ontology design, and we illustrate a preliminary proposal for a top-level ontology develped according to such principles. As a concrete example of ontology-based information retrieval, we finally report an ongoing experience of use of a large linguistic ontology for the retrieval of object-oriented software components.