The Physiome Model Repository (PMR) is a collection of physiological and anatomical models written in XML based form. The PMR goal is to provide a robust platform for scientists in the biology-related domain such as bioengineering and biomedical so they can reuse, reproduce, collaborate, and exchange simulation experiments consistently and unambiguously. The stored models consist of elements of mathematical equations along with all variables, and description. Currently, a large number of elements has been annotated using ontology URIs and has been stored as RDF triples for easy management and retrieval. By using SPARQL, scientists are able to find relevant elements and use these for their works. However, the use of SPARQL in PMR needs sufficient knowledge about ontology URIs and elements needed which may cause difficulties. Therefore, we have developed an automatic annotation to map the user’s text query to ontology URIs. We have utilised textual information inside the PMR and ontology URIs' label, definition, and synonym from BioPortal to extract text-based features. We have also used the NLP parser to divide the query into candidate phrases. Utilising these features, we are able to annotate the candidate phrases and then select the final phrases with relatively high accuracy.