  Many concept-to-text generation systems require domain-specific linguistic
resources to produce high quality texts, but manually constructing these
resources can be tedious and costly. Focusing on NaturalOWL, a publicly
available state of the art natural language generator for OWL ontologies, we
propose methods to extract from the Web sentence plans and natural language
names, two of the most important types of domain-specific linguistic resources
used by the generator. Experiments show that texts generated using linguistic
resources extracted by our methods in a semi-automatic manner, with minimal
human involvement, are perceived as being almost as good as texts generated
using manually authored linguistic resources, and much better than texts
produced by using linguistic resources extracted from the relation and entity
identifiers of the ontology.
