Upper Modeling: organizing knowledge for natural language processing

Abstract

A general, reusable computational resource has been de- veloped within the Penman text generation project for organizing domain knowledge appropriately for linguistic realization. This resource, called the upper model, provides a domain- and task-independent classification system" that supports sophisticated natural language processing while significantly simplifying the interface between domain-specific knowledge and general linguis- tic resources. This paper presents the results of our experiences in designing and using the upper model in a variety of applications over the past 5 years. In particular, we present our conclusions concerning the ap- propriate organization of an upper model, its domain- independence, and the types of interrelationships that need to be supported between upper model and gram- mar and semantics.