Fast, Scalable and Reliable Generation of Controlled Natural Language

In this paper we describe a natural language generation system which takes as its input a set of assertions encoded as a semantic graph and outputs a data structure connecting the se-mantic graph to a text which expresses those assertions, encoded as a TAG syntactic tree. The scope of the system is restricted to con-trolled natural language, and this allows the generator to work within a tightly restricted domain of locality. We can exploit this fea-ture of the system to ensure fast and efficient generation, and also to make the generator re-liable by providing a rapid algorithm which can exhaustively test at compile time the com-pleteness of the linguistic resources with re-spect to the range of potential meanings. The system can be exported for deployment with a minimal build of the semantic and linguistic resources that is verified to ensure that no run-time errors will result from missing resources. The framework is targeted at using natural lan-guage generation technology to build semantic web applications where machine-readable in-formation can be automatically expressed in natural language on demand.