Task Description for PASCAL Challenge Evaluating Ontology Learning and Population from Text Contact Person

Ontologies are formal, explicit specifications of shared conceptualizations, representing concepts and their relations that are relevant to a given domain of discourse. Currently, ontologies are mostly developed as well as used through a manual process, which is very ineffective and may cause major barriers to their large-scale use in such areas as Knowledge Discovery and Semantic Web. As human language is a primary mode of knowledge transfer, linguistic analysis of relevant documents for this purpose seems a viable option. More precisely, automation of ontology construction (ontology learning) and use (ontology population through knowledge markup) can be implemented by a combined use of linguistic analysis and machine learning approaches for text mining.