Strategies for Comparison in Encyclopmdia Descriptions

Comparisons are typically employed to distinguish similar entities, or to illustrate a property of an entity by referring to another com• monly known entity which shares that property. Based on an analysis of a corpus of encyclopaedia texts, we define three types of comparisons and outline some strategies for applying these in the generation of entity descriptions. We describe how these comparison strategies are used within the PEBA-II hypertext generation system to generate descriptions of animals. 1 I n t r o d u c t i o n a n d A i m s In this paper, we outline some strategies for comparison which we use in PEBA-II, a hypertext generation system which produces encyclopaedia descriptions of entities as World Wide Web ( w w w ) documents, based on an underlying taxonomic knowledge base. PEBA-II is part of a larger research programme built around the idea of an intelligent on-line encyclopaedia, where the descriptions produced by the system vary for different users and at different times. Our work is grounded in the domain of animal descriptions, although similar issues arise in many other domains. Comparisons are widespread within existing encyclopaedia descriptions. In particular, when describing a new concept to a user, a comparison may be made with reference to other known concepts or ideas, enabling the hearer to more easily process and understand the new material (see [Milosavljevic 1996]). So, for example, in the context of animal descriptions, if the user knows about the porcupine and requests a description of the echidna, then we might describe the echidna by highlighting both its similarities to and differences from the porcupine. Clearly this requires us to make use of some notion of a user model, and in a way that is distinct from previous work in user-modelling in text generation. Our aim is to produce texts which introduce new concepts by reference to existing knowledge the user is assumed to have, thus employing the user model to greater advantage; past research (see, in particular, [Paris 1987]) has concentrated on avoiding the production of texts which repeat what the user already knows. By making use of a discourse model, we can also generate comparisons that take account of entities that have been mentioned in the previous discourse. This is particularly important in the context of the dynamic construction of hypertext documents from an underlying representation: by employing text generation techniques, we can produce context-dependent descriptions which vary depending on the information which has already been presented to the user, thus overcoming some of the limitations of hypertext documents which have been constructed simply by breaking an existing linear text into