A proposal of knowledge representation about ontology population from texts written in natural language

Resumen

Ontologies are referred to shared conceptualizations with several elements—e.g., domains, concepts, instances, relations, and attributes—to be used in computational inference. Ontology population is referred to both extraction and classification of instances belonging to classes and relations defined in the ontology from any information sources. State-of-the-art review exhibits some proposals for representing ontology population, but they are incomplete and exhibit some drawbacks. Ontology population process is hard, and it requires a good knowledge representation. In this paper we propose a pre-conceptual schema for representing ontology population. We evaluate knowledge representation by using five fundamental roles: i) as a surrogate of reality; ii) as a set of ontological commitments; iii) as a fragmentary theory of intelligent reasoning; iv) as a medium for efficient computation; and v) as a medium of human expression. This contributes to a better understanding of the ontology population process and demonstrates the benefits of using a pre-conceptual schema to enhance clarity, reduce ambiguity, and organize knowledge. Finally, it contributes to the main objective of ontologies, i.e., sharing knowledge.