  Competency Questions (CQs) for an ontology and similar artefacts aim to
provide insights into the contents of an ontology and to demarcate its scope.
The absence of a controlled natural language, tooling and automation to support
the authoring of CQs has hampered their effective use in ontology development
and evaluation. The few question templates that exists are based on informal
analyses of a small number of CQs and have limited coverage of question types
and sentence constructions. We aim to fill this gap by proposing a
template-based CNL to author CQs, called CLaRO. For its design, we exploited a
new dataset of 234 CQs that had been processed automatically into 106 patterns,
which we analysed and used to design a template-based CNL, with an additional
CNL model and XML serialisation. The CNL was evaluated with a subset of
questions from the original dataset and with two sets of newly sourced CQs. The
coverage of CLaRO, with its 93 main templates and 41 linguistic variants, is
about 90% for unseen questions. CLaRO has the potential to facilitate
streamlining formalising ontology content requirements and, given that about
one third of the competency questions in the test sets turned out to be invalid
questions, assist in writing good questions.
