Ontologies are widely used in text technology and artificial intelligence. The need to develop large ontologies for real-life applications provokes researchers to automate ontology extension procedures. Automatic updates without the control of a human expert can generate potential conflicts between original and new knowledge. As a consequence the resulting ontology can yield inconsistencies. We propose a procedure that models the process of adapting an ontology to new information by repairing several important types of inconsistencies.