CLOnE: controlled language for ontology editing
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Naturalness vs. predictability: a key debate in controlled languages
CNL'09 Proceedings of the 2009 conference on Controlled natural language
Implementing controlled languages in GF
CNL'09 Proceedings of the 2009 conference on Controlled natural language
Involving business users in formal modeling using natural language pattern sentences
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
Automated verbalization for ORM 2
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
A knowledge infrastructure for the dutch immigration office
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
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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.