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<Paper uid="C86-1040">
  <Title>The Role of Inversion and PP-Fronting In Relating Discourse Elements: some implications for cognitive and computational models of Natural Language Processing</Title>
  <Section position="5" start_page="171" end_page="172" type="metho">
    <SectionTitle>
4. The Experiment
</SectionTitle>
    <Paragraph position="0"> In the above two sections we briefly motiw~ted and developed an analysis of the organization of discourse representations. Basically the analysis claimed that each discourse representation, no matter how it is represented, i.e. what particular theory or formalism, were indexed via their focused NPs. The analysis also claimed that non-SVO word structure was a signal to search through the labels to locate the structure in which to embed the representation currently being processed.</Paragraph>
    <Paragraph position="1"> There are two aspects of this analysis that we will focus on in this section: the creating of labels and the searching of the labels. The more complicated aspects of building and embedding, or relating, the strnctnrcs to one another will be iguored for the sake of exposition.</Paragraph>
    <Paragraph position="2"> A simple experiment was performed to explore the computational usefulness of the proposed labeling system.</Paragraph>
    <Paragraph position="3"> Three programs werc written in Symbolics \]?rolog. Each program processed a set of twenty-six sentences and created discourse representations. To create the discourse representations the DRS construction algorithm found iu Kamp (1986) was used. Added to this were straightforward rules for creating DRSs for locative prepositional phrases. The task for each program was to resolve simple anaphora by searching through the discourse representations for the antecedent. A straightforward feature matching technique was used to do this. If one were trying to resolve the reference for a pronoun and a full NP then only the features of the lexieal item, e.g. masculine, singular, was matched. If the reference for a full NP was being resolved then the whole lexical item was search for.</Paragraph>
    <Paragraph position="4"> The first program only constructed discourse representations. it did not construct labels as well. Thus whenever anaphoric resolution was called for by thc DRS Construction algorithm, this program had to search through thc cntire data basc until a match was found. The second program created labels but they were only searched when the sentences being processed had non-SVO structure. The third program created labels as well but it only searched the labels. That is the heuristic always applied.</Paragraph>
    <Paragraph position="5"> Each DRS was a flat list. Each label list was also flat. Before each run of the program the machine was cokl booted.</Paragraph>
    <Paragraph position="6"> The data was a list of 24 sentences. The l~st sentence contained the only fronted PP, which referred back to the first sentence. The results of this experiment are discussed in the next section.</Paragraph>
  </Section>
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