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<Paper uid="J99-2001">
  <Title>A Methodology for Extending Focusing Frameworks</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
1. Introduction
</SectionTitle>
    <Paragraph position="0"> The central problem addressed in this work is how to develop and assess algorithms for tracking local focus and for proposing referents of pronouns for use in natural language processing (NLP) systems. 1 By &amp;quot;local focus,&amp;quot; we refer to the person, object, property, or concept that a sentence is most centrally about within the discourse context in which it occurs. The appropriate movement and marking of local focus, and the appropriate choice of the form of a noun phrase (NP) based on local focus information, are considered to contribute to the local coherence exhibited by discourse (Sidner \[1979\], Grosz, Joshi, and Weinstein \[1983, 1995\], Carter \[1987\], and others).</Paragraph>
    <Paragraph position="1"> In addition, local focus information is one source of information that is used by readers and hearers for interpreting pronouns. Some researchers (e.g., Hobbs 1978; Lappin and Leass 1994) have proposed pronoun resolution algorithms that do not involve focus tracking. However, our view is that local focus tracking and pronoun resolution are mutually dependent processes. The local focus information influences pronoun resolution, and pronoun resolution, in turn, influences updating focus information. Therefore, the tracking of local focus is crucial for the interpretation of pronouns.</Paragraph>
    <Paragraph position="2">  1 This research was supported by NSF grants #IRI-9010112 and #IRI-9416916, the Nemours Foundation, a Unidel Summer Research Fellowship from the Department of Computer and Information Sciences at the University of Delaware, and NSF Graduate Traineeship grant #GER-9354869.</Paragraph>
    <Paragraph position="3"> (~) 1999 Association for Computational Linguistics  Computational Linguistics Volume 25, Number 2 There have been several algorithms described in the literature for tracking local focus information and for using this tracked information to do pronoun resolution. In this paper we first briefly introduce the notion of local focusing and what a local focusing algorithm is intended to capture. Generally the way that the focus of a sentence is expected to shift through a discourse is dependent on some syntactic properties of the sentence. However, most of the work on tracking local focus has concentrated on simple (single clause) sentences. Thus previous work on focusing has not adequately addressed the processing of complex (i.e., multiclausal) sentences. We discuss a number of issues involved in the processing of complex sentences in order to motivate the need for a methodology for extending focusing frameworks to handle them. We review a methodology used by other researchers to develop their focusing frameworks, and we identify some difficulties with that methodology. We examine the possibility of using a corpus analysis to extend a focusing framework, and briefly describe potential problems with such an approach. We then introduce our own two-part methodology for extending focusing frameworks, which we call the Semantically Slanted Discourse (SSD) Methodology. The first part of the methodology consists of an exploratory phase in which possible extensions to a focusing algorithm are discovered through the use of carefully constructed discourses that rely on the potential tension between focusing and world-knowledge factors in pronoun resolution. We show how this first phase can be used to propose an extension to a local focusing framework in order to handle a given type of complex sentence. The first phase is then followed by a corpus analysis to confirm its findings. We explain why a corpus analysis used to confirm an extension is more practical than one used to identify an extension in the first place.</Paragraph>
  </Section>
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