Natural language understanding applications are good candidates to solve the knowledge acquisition bottleneck when designing large scale concept systems. However, a necessary condition is that systems are built that transform sentences into a meaning representation that is independent of the subtleties of linguistic structure that nevertheless underly the way language works. The Cassandra II syntactic-semantic tagging system fulfills this goal partially. Within the GALEN-IN-USE project, it is used to transform linguistic representations of surgical procedure expressions into conceptual representations. In this paper, the proctology chapter of the SNOMED V3.1 procedure axis was used as a testbed to evaluate the usefulness of this approach. A quantitative and qualitative analysis of the data obtained is presented, showing that the Cassandra system can indeed complement the manual modelling efforts being conducted in the GALEN-IN-USE project. The different requirements related to linguistic modelling versus conceptual modelling can partly be accounted for by using an interface ontology, of which the fine tuning will however remain an important effort.