OntoUML, an ontology-driven conceptual modelling language based on the Unified Foundational Ontology (UFO), has been demonstrated to have superior clarity in comparison to other commonly used modeling languages, as supported by empirical evidence. Furthermore, the use of RDF technology has led to the creation of the gUFO ontology, enabling the interoperability and reuse of RDF tools, thereby providing new opportunities to explore and evaluate large OntoUML/UFO models and their instances/data. This study utilizes the SPARQL query language to evaluate the quality of OntoUML models and develop queries for identifying and retrieving instances of anti-patterns defined for OntoUML. The effectiveness of these queries is assessed by applying them to a set of conceptual models of varying complexity that have been captured using gUFO.