| Abstract: | Previous work in natural language génération has exploited discourse focus to guide the selection of propositional content and the génération of referring expressions (e.g., pronominalization, définite noun phrase génération). However, there are many other sources of contextual information which can be used to constrain linguistic realization. The realization of certain classes of temporal and spatial référents, for example, can be guided by more detailed models of time and space. Therefore, this article first identifies a number of contextual coordinates or points of référence (known as indexicals in linguistics). Next, we formalize three of these contextual coordinates – topic, time, and space – in a computational model. In doing so, the article describes the use of a Reichenbachian temporal model which is exploited to guide the realization of verb tense and aspect as well as the realization of temporal référents (e.g., temporal connectives and adverbials such as "meanwhile" and "ten minutes later"). The article then describes a spatial model which is used to guide the linguistic realization of spatial référents (e.g., "here,""there") and spatial adverbials (e.g., "two miles away"). We discuss the relation between these temporal and spatial models and illustrate their use in generating text from two different application systems. We find that the combined use of topical, temporal, and spatial contextual coordinates enhances the fluency, connectivity, and conciseness of the resulting text. |
