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<Paper uid="A88-1025">
  <Title>AUTOMATICALLY GENERATING NATURAL LANGUAGE REPORTS IN AN OFFICE ENVIRONMENT</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1. INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> This paper describes the implementation of a text generating system which produces natural language reports on the status of a system of inter-related processes at various stages of progress. The motivations behind this project were to model a system of concurrent processes and to successfully generate well-formed text about their temporal behavior. We view a process as an ordered sequence of events over time where an event refers to an atomic action by one of the participating agents. In many AI applications, monitoring the state of a system of processes is deemed essential.</Paragraph>
    <Paragraph position="1"> The ability of a system in such an environment to describe its actions in natural language will be certainly very useful.</Paragraph>
    <Paragraph position="2"> As our sample domain, we chose a scenario where the system is used to assist the secretary for an academic journal by keeping track of a paper submitted for publication. The process being modeled is that of paper-submission with the usual participating agents being the author of the paper, the journal editor, the reviewers assigned to evaluate the paper and the journal secretary.</Paragraph>
    <Paragraph position="3"> In the rest of the paper we present methods to represent the knowledge of the chosen domain, to model historical knowledge base of events and processes, to appropriately order the contents of the historical information store for presentation based on temporal relationships and other relevant factors, and to produce coherent English text describing the events in the domain. The system as described herein has been fully implemented, and currently avenues for further improvement are actively being pursued.</Paragraph>
    <Paragraph position="4"> Section 2 of this paper gives a brief description of the domain being modeled along with an overview of the system components. Section 3 describes the representation of the processes in terms of a network of rules. Section 4 elaborates the nature of the historical information store. Section 5 deals with text planning which is crucial for selecting information to be presented in a coherent manner. Section 6 details the actual process of text generation. Finally, we conclude with a discussion about enhancements to the existing system which can contribute towards a more general implementation with the added power of expected future inference and and the ability to reason about viewpoints of agents external to the system.</Paragraph>
    <Paragraph position="5"> Further details about the system's design and implementation, and other relevant discussions can be found in \[Kalita 86\].</Paragraph>
  </Section>
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