A module for generation of referring expressions (GRE) derives descriptions that identify specified entities in context. In the implemented system I describe here for specifying simple cases of GRE by example, system-builders pair entities with descriptions of them that would be satisfactory for a system to use in context. Automatic methods then construct a suitable knowledge base and context set for a knowledge-based GRE module for the system. These resources will always account for the sample descriptions the designer has supplied, but can also generalize to other possible referring expressions in other possible contexts in the application. I discuss the results in the perspective of knowledge-acquisition methodology for NLG for dialogue, draw contrasts with other uses of examples in NL technology, and use the results to argue for constrained models of the generation process founded on declarative links between resources and generator output.