Enhancing Explanation Coherence With Rhetorical Strategies

ENHANCING EXPLANATION COHERENCE WITH RHETORICAL STRATEGIES MARK T. MAYBURY Rome Air Development Center Intelligent Interface Group Griffiss AFB, Rome NY 13441-5700 maybury@radc-tops20.arpa and Cambridge University Computer Laboratory Cambridge, England CB2 3QG ABSTRACT This paper discusses the application of a previously reported theory of explanation rhetoric (Maybury, 1988b) to the task of explaining constraint violations in a hybrid rule/frame based system for resource allocation (Dawson et al, 1987). This research illustrates how discourse strategies of explanation, textual connectives, and additional justification knowledge can be applied to enhance the cohesiveness, structure, and clarity of knowledge based system explanations. INTRODUCTION Recent work in text generation includes emphasis on producing textual presentations of the explanations of reasoning in knowledge-based systems. Initial work (Swartout, 1981) on the direct translation of underlying system knowledge led to insights that more perspicuous justifications would result from keeping track of the principles or deep causal models which supported that knowledge (Swartout and Smoliar, 1988). And experiments with discourse strategies demonstrated the efficacy of the rhetorical organization of knowledge to produce descriptions, comparisons (McKeown, 1985) and clarification (McCoy, 1985). Researchers have recently observed (Paris et al, 1988) that the line of explanation should not isomorphically mirror the underlying line of reasoning as this often resulted in poorly connected text (Appelt, 1982). Others have attempted to classify patterns of explanations (Stevens and Steinberg, 1981; Schank, 1986). The approach presented here is to exploit generic explanation strategies and focus models (Sidner, 1983; Grosz and Sidner, 1988) to organize the back-end justification via an explanation rhetoric -- that is, a rhetorical model of strategies that humans employ to persuade, support, or clarify their position. The result is a more connected, flowing and thus easier to follow textual presentation of the explanation. KNOWLEDGE REPRESENTATION and EXPLANATION Previous research in natural language generation from knowledge based systems has primarily focused on independent knowledge representation schemes (e.g rule, frame or conceptual dependency formalisms). In contrast, the application chosen to test the concepts of rhetorical explanations is an FRL (Roberts and Goldstein, 1977) based mission planning system for the Air Force which utilizes both rules and frames during decision-making. Hence, the explanations concern rule-based constraint violations which result from inference about entities in the knowledge base, their attributes, and relationships. For example, if the user plans an offensive counter air mission with an incompatible aircraft and target, the system will automatically signal a constraint violation via highlighting of objects on the screen. If the user mouses for explanation, the system will state the conflicting rule, then list the supporting knowledge, as shown in figure 1. - 168 - The choice for AIRCRAFT is in question because: BY TARGET-AIRCRAFr-1:1 THERE IS A SEVERE CONFLICT BETWEEN TARGET AND AIRCRAFT FOR OCA10022 1. THE TARGET OF OCA1002 IS BE307033 2. BE30703 RADIATES 3. THE AIRCRAFT OF OCA1002 IS F-111E 4. F- 111E IS NOT A F-4G Figure 1. Current Explanation of Rule Violation The weak textuality of the presentation manifests itself through ungrammatical sentences and the implicit suggestion of relationships …

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