Abstract
Involving domain experts in modeling is important when knowledge needs to be captured in a model and only domain experts can establish whether the models are correct. We have experienced that a natural language based representation of a model helps them to understand the semantics of a model and has advantages over a visual representation. Therefore a controlled natural language (CNL) is designed for our existing semantic reasoning tool Be Informed, which is based on conceptual graphs. The resulting CNL has a formal logical basis but the goal of the CNL representation is to improve readability for human readers. We report on the challenge to develop a CNL that 1) is easy and intuitively readable for domain experts with no background in formal logics, 2) can be easily generated from the formal representation and 3) can be easily adjusted for other natural languages and cultural preferences. The solution uses patterns to represent the CNL that map to the conceptual graph. The patterns are based on SBVR’s RuleSpeak and can be easily adjusted for local differences.
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Spreeuwenberg, S., van Grondelle, J., Heller, R., Grijzen, G. (2012). Using CNL Techniques and Pattern Sentences to Involve Domain Experts in Modeling. In: Rosner, M., Fuchs, N.E. (eds) Controlled Natural Language. CNL 2010. Lecture Notes in Computer Science(), vol 7175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31175-8_10
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DOI: https://doi.org/10.1007/978-3-642-31175-8_10
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