Using Plausible Inference Rules in Description Planning

USING PLAUSIBLE INFERENCE RULES IN DESCRIPTION PLANNING Alison Cawsey* Computer Laboratory, University of Cambridge New Museum~ Site, Pembroke St, Cambridge, England. ABSTRACT Current approaches to generating multi-sentence text fail to consider what the user may infer from the dif- ferent statements in a description. This paper presents a system which contains an explicit model of the infer- ences that people may make from different statement types, and uses this model, together with assumptions about the user's prior knowledge, to pick the most ap- propriate sequence of utterances for achieving a given communicative goal. INTRODUCTION Examples, analogies and class identification are used in many explanations and descriptions. Yet current text generation techniques all fail to tackle the problem of when an example, analogy or class is appropriate, what example, analogy or class is best, and exactly what the user may infer from a given example, analogy or class. McKeown, for example, in her identification schema (given in fig- ure 1) includes the 'rhetorical predicates' identi- fication (as an instance of some class), analogy, particular.illustration and attributive (McKeown, 1985). From each of these, different information could be inferred by the user. In a human expla- nation they might be used to efficiently convey a great deal of information about the object, or to reinforce some information about an object so it may be better recalled. Yet in McKeown's schema based approach the only mechanism for selecting between these different explanation options is the *This work was carried out while the author was at the department of Artificial Intelligence, University of Edin- burgh, funded by a post doctoral fellowship from the Science and Engineering Research Council. Thanks to Ehud Re- iter, Paul Brna and to the anonymous reviewers for helpful comments. Identification (class &: attribute/function) (Analogy/Constituence/At tributive/Renaming/ Amplification}* Particular-Illustration/Evidence+ { Amplification/Analogy/At tributive) {Particular-Illustration/Evidence) Note: '()' indicates optionality, '/' alternatives, '+' that item may appear 1-n times, '*' 0-n times. Figure 1: McKeown's identification schema [McKeown 851 initial pool of knowledge available to be conveyed, and focus rules, which just enforce some local co- herence on the discourse. A particular example or analogy could perhaps be selected using the func- tions interfacing the rhetorical predicates to the do- main knowledge base, but this is not discussed in the theory. More recently, Moore has included examples, analogies etc. in her text planner (Moore, 1990). She includes planning operators to deseribe- by-superclass, describe-by-abstraction, describe-by- ezample, describe-by-analogy and describe-by.parts- and.use. Two of these are illustrated in figure 2. But again there are no principled ways of selecting which strategy to use (beyond, for example, possi- bly selecting an analogy if the analogous concept is known), and the effect of each strategy is th~ same - that the relevant concept is 'known'. In re- ality, of course, the detailed effects of the different strategies on the hearer'e knowledge will be very different, and will depend on their prior knowl- 119 - (define-text-plan-operator :NAME describe-by-example :EFFECT (BEL ?hearer (CONCEPT ?concept)) :CONSTRAINTS (AND (ISA ?concept OBJECT) (IMMEDIATE-SUBCLASS ?example ?concept)) :NUCLEUS …

Content truncated to 500 words