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<Paper uid="W93-0220">
  <Title>References</Title>
  <Section position="4" start_page="72" end_page="75" type="ackno">
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Abstract
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    <Paragraph position="0"> This position paper contrasts rhetorical structuring of propositions with intentional decomposition using communicative acts. We discuss the kinds of information current explanation planners capture in their plan operators and propose extensions to these. In Maybury (1992b) we detail how these plans can and have been extended to capture a more general notion of communication as action, describing other types of communicative acts such as graphical acts and discourse acts. Our current efforts (Maybury, 1992b, forthcoming) are focused on developing a taxonomy of multimedia communication acts which attempt to distinguish semantic relations, rhetorical relations and intentions.</Paragraph>
    <Paragraph position="1"> Rhetorical Structuring versus Intention Decomposition A number of researchers have investigated using structural analyses of text, including Rhetorical Structure Theory (RST) (Mann and Thompson. 1987), as the basis for explanation planning architectures. For example, using rhetorical relations such as background and elaboration, Hovy's (1988) system constructs a rhetorical structure over a given set of propositions (See Figure la). Moore's (1989) system also constructs a rhetorical structure, however, the leafnodes of the resulting tree are illocutionary acts (e.g., inform) with associated propositions. While we agree that text contains relations between parts, we also concur with the position held by Suthers (1991) and others that rhetorical relations, in their current form, conflate a number of issues including intention, structure, linear precedence, and epistemological distinctions. Hovy (1990) details problems with R,ST approaches to paragraph planning, including algorithnfic problems and, more seriously, problems with the theory and representation of coherence relations.</Paragraph>
    <Paragraph position="2"> In contrast to RST-based planners but similar to rhetorical schema based generators, our explanation planning architecture uses &amp;quot;rhetorical predicates&amp;quot; (e.g., attribution, evidence, enablement) to abstractly characterize epistemological content and relations in tile underlying knowledge base. As in MeKeown (1982), some of these predicates indicate local relations (e.g., illustration) and have associated cue words (e.g., &amp;quot;for example&amp;quot;) or associated semantic actions (e.g., &amp;quot;contains,&amp;quot; &amp;quot;enables&amp;quot;). Ilowever, other predicates, such as attribution or definitiou, have no marked relation to their surrounding text (only the weak notion of elaboration). In our attempts to geuerate the range of text l.ypes ranging from narration to argumeut, we have found tile need to develop a correspondingly broad range of rhetorical predicates, including logical-definition, synonymic-definition, constituency, cb~ssification, evidence, motivation, etc.</Paragraph>
    <Paragraph position="3"> *Mail Stop K329, Artificial Intelligence Center, The MITRE Corporation, Burlington Road, Bedford, MA 01730. (617) 271-7230. maybury@linus.mitre .org.</Paragraph>
    <Paragraph position="4">  We use these same rhetorical predicates to abstractly mark the epistemological content of speech acts (e.g., request or inform). All example action in our system might be II~FORX(#&lt;systora&gt;, #&lt;usor-023&gt;, logical-do:finition(#&lt;ForrarJ.-Testarossa&gt;)) which says &amp;quot;have tile system inform user-023 of the logical definition of tile object, #&lt;Ferrar:i.-Testarossa&gt;,&amp;quot; which might eventuaily result in the utterance &amp;quot;A Ferrari Testarossa is a fast, sleek Italian sports car&amp;quot;. In order to retrieve the content for a &amp;quot;logical definition&amp;quot; predicate, we must not only look up the genus of the entity, but also calculate its differentia, or distinguishing characteristics (Maybury, 1990). Thus, the relation between rhetorical predicates and semantic relations in the underlying knowledge base is not a simple one-to-one mapping; in some cases the content must be calculated. Moreover, content may be modulated by context or by a user model (e.g., choosing the perspective from which to view an object., if it has multiple superordinates (McCoy, 1985)).</Paragraph>
    <Paragraph position="5"> Our architecture actually distinguishes between illocutionary acts (e.g., inform, request) and surface speech/locutionary acts (e.g., assert,, command, suggest) which have associated surface forms (e.g., declarative imperative, interrogative mood). In our architecture, the organization and structure of illocutionary speech acts such as the above inform action is accomplished by more abstract rhetorical acts (e.g., describe, compare, argue). Rhetorical acts characterize the communicative action performed by one or more utterances, and correspond to the text types such as description, narration, and exposition. Because our focus has been on formalizing the communicative actions that underlie texts, we have worked toward a unified view of rhetorical and speech acts. Therefore, our approach can be seen as an extension of theoretical work which views language as purposeful behavior (Austin, 1962; Searle, 1969) and of computational implementations of speech acts (Cohen, 1978; Allen, 1979; Appelt, 1982). As we dicuss below, we have also investigated using the notio, of rhetorical acts to characterize both linguistic and non-linguistic acts, resulting, for example, in mixed text and graphics.</Paragraph>
    <Paragraph position="6"> We formalize conmlunicative acts (speech acts and rhetorical acts) ms plan operators. A hierarchical planner reasons about these operators in order to produce a text plan (an executable action decomposition) that achieves some given discourse goal (see Figure l b). The plamler actually produces two structures: the action decoml)ositio, shown in Figure lb as well as a corresl)oudiug effect decolUl)Osition in which each level represe.ts to the effects achieved by each act in the actio, dccompositio.. In the architecture implemented in our system TEXPLAN, the decomposition of plan operators captures the hierarchical structure and order of intentions underlying text. Thus our architecture differs from work in planned rhetorical relations (Hovy, 1988; Moore, 1989) in that it recog.izes and formalizes the distinction between the rhetorical relations in a text (e.g., evidence, enablcment, purpose) and the rhetorical acts establishing these. And as we will discuss in a detailed positio.</Paragraph>
    <Paragraph position="7"> paper, there are also differences in the representation of preconditions and effects.</Paragraph>
    <Paragraph position="8">  In our research we have found that there are at least four generic types of text: description, narration, exposition, and argument. These text types form the basis of explanations which convey different propositional content (e.g., entities and relations versus events and states), have particular intended effects on the addressee's knowledge, beliefs, and desires, and are compositional (e.g., narration can invoke description). In the extended position paper wc contrast two architectures for explanation planning: rhetorical structuring of propositions versus comnmnicative act-based explanation planning. In our work we consider the structure of plan operators, including issues of constraints, preconditions, effects, and decomposition, and have discussed (Maybury, 1992b) how current representations might be extended, and also consider the applicability to plan inultimedia exldanations and discourse. After considering issues concerning plans and focus models, we conclude hy indicating that current plan-based architectures suffer from a number of fundamental architectural deficiencies that stem froln the current state of the art in planning techniques. This situation is exacerbated by the current lack of understanding of the nature of and relationshiip among attention, intensions and rhetorical relations.</Paragraph>
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