  To achieve a flexible and adaptable system, capability ontologies are
increasingly leveraged to describe functions in a machine-interpretable way.
However, modeling such complex ontological descriptions is still a manual and
error-prone task that requires a significant amount of effort and ontology
expertise. This contribution presents an innovative method to automate
capability ontology modeling using Large Language Models (LLMs), which have
proven to be well suited for such tasks. Our approach requires only a natural
language description of a capability, which is then automatically inserted into
a predefined prompt using a few-shot prompting technique. After prompting an
LLM, the resulting capability ontology is automatically verified through
various steps in a loop with the LLM to check the overall correctness of the
capability ontology. First, a syntax check is performed, then a check for
contradictions, and finally a check for hallucinations and missing ontology
elements. Our method greatly reduces manual effort, as only the initial natural
language description and a final human review and possible correction are
necessary, thereby streamlining the capability ontology generation process.
