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

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.