Using aggregation for selecting content when generating referring expressions

Using aggregation for selecting content when generating referring expressions John A. Bateman Sprach- und Literaturwissenschaften University of Bremen Bremen, Germany e-mail: bateman0un±-bremen, de Abstract Previous algorithms for the generation of re- ferring expressions have been developed specif- ically for this purpose. Here we introduce an alternative approach based on a fully generic ag- gregation method also motivated for other gen- eration tasks. We argue that the alternative contributes to a more integrated and uniform approach to content determination in the con- text of complete noun phrase generation. 1 Introduction When generating referring expressions (RE), it is generally considered necessary to provide suf- ficient information so that the reader/hearer is able to identify the intended referent. A num- ber of broadly related referring expression al- gorithms have been developed over the past decade based on the natural metaphor of 'ruling out distractors' (Reiter, 1990; Dale and Had- dock, 1991; Dale, 1992; Dale and Reiter, 1995; Horacek, 1995). These special purpose algo- rithms constitute the 'standard' approach to determining content for RE-generation at this time; they have been developed solely for this purpose and have evolved to meet some spe- cialized problems. In particular, it was found early on that the most ambitious RE goal-- that of always providing the maximally concise referring expression necessary for the context ('full brevity')--is NP-haxd; subsequent work on RE-generation has therefore attempted to steer a course between computational tractabil- ity and coverage. One common feature of the favored algorithmic simplifications is their in- crementality: potential descriptions are succes- sively refined (usually non-destructively) to pro- duce the final RE, which therefore may or may not be minimal. This is also often motivated on grounds of psychological plausibility. In this paper, we introduce a completely different metaphor for determining RE-content that may be considered in contrast to, or in combination with, previous approaches. The main difference lies in an orientation to the organization of a data set as a whole rather than to individual components as revealed dur- ing incremental search. Certain opportunities for concise expression that may otherwise be missed are then effectively isolated. The ap- proach applies results from the previously unre- lated generation task of 'aggregation', which is concerned with the grouping together of struc- turally related information. 2 The aggregation-based metaphor Aggregation in generation has hitherto gener- ally consisted of lists of more or less ad hoc, or case-specific rules that group together paxticu- lax pre-specified configurations (cf. Dalianis and Hovy (1996) and Shaw (1998)); however Bate- man et al. (1998) provide a more rigorous and generic foundation for aggregation by applying results from data-summarization originally de- veloped for multimedia information presenta- tion (Kamps, 1997). Bateman et al. set out a general purpose method for constructing ag- gregation lattices which succinctly represent all possible structural aggregations for any given data set. 1 The application of the aggregation- based metaphor to RE-content determination is motivated by the observation that if some- thing is a 'potential distractor' for some in- tended referent, then it is equally, …

Content truncated to 500 words