An Algorithm for Generating Referential Descriptions with Flexible Interfaces

An Algorithm For Generating Referential Descriptions With Flexible Interfaces Helmut Horacek Universit/it des Saarlandes FB 14 Informatik D-66041 Saarbrticken, Deutschland horacek@cs.uni-sb.de Abstract Most algorithms dedicated to the generation of referential descriptions widely suffer from a fundamental problem: they make too strong assumptions about adjacent processing components, resulting in a limited coordination with their perceptive and linguistics data, that is, the provider for object descriptors and the lexical expression by which the chosen descriptors is ultimately realized. Motivated by this deficit, we present a new algorithm that (1) allows for a widely unconstrained, incremental, and goal-driven selection of descriptors, (2) integrates linguistic constraints to ensure the expressibility of the chosen descriptors, and (3) provides means to control the appearance of the created referring expression. Hence, the main achievement of our approach lies in providing a core algorithm that makes few assumptions about other processing components and improves the flow of control between modules. 1 Introduction Generating referential descriptions I requires selecting a set of descriptors according to criteria which reflect humans preferences and verbalizing these descriptors while meeting natural language constraints. Over the last decade, (Dale, 1989, Dale, Haddock, 1991, Reiter, 1990b, Dale, Reiter, 1995), and others 2 have contributed to this issue The term 'referential description' is due to Donellan (Donellan, 1966). This notion signifies a referring expression that serves the purpose of letting the hearer identify a particular object out of a set of objects assumed to be in the current focus of attention. The approach undertaken by Appelt and Kronfeld (Appelt, 1985a, Appelt, 1985b, Kronfeld, 1986, Appelt, Kronfeld, 1987) is very elaborate but it suffers from very limited coverage, missing assessments of the relative benefit of alternatives, and notorious inef- ficiency. (see the systems NAOS (Novak, 1988), EPICURE (Dale, 1988), FN (Reiter, 1990a), and IDAS (Reiter, Dale, 1992)). Nevertheless, these approaches still suffer from some crucial deficits, including limited coverage (see (Horacek, 1995, Horacek, 1996) for an improved algo- rithm), and too strong assumptions about adjacent processing components, namely: • the instant availability of all descriptors for an object to be described, • the adequate expressibility of a chosen set of descriptors in terms of lexical items. Motivated by the resulting deficits, we develop a new algorithm that does not rely on these assumptions. It (1) allows for a widely unconstrained, incremental, and goal- driven selection of descriptors, (2) integrates linguistic constraints to ensure the expressibility of the chosen descriptors, and (3) provides means to control the appear- ance of the created referring expression. This paper is organized as follows. After having introduced some basic terminology, we elaborate interface deficits of existing algorithms, form which we derive desi- derata for an improved algorithm. Then we describe concepts to meet these desiderata, and we illustrate their operationalization in a schematic and in a detailed version. Finally, we demonstrate the increased functionality of the new algorithm, and we evaluate the achievements. 2 Terminology Used In the scope of this paper, we adopt the terminology originally formulated in (Dale, 1988) and …

Content truncated to 500 words