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<Paper uid="C86-1111">
  <Title>A New Predictive Analyzer of English</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1. Introduction
</SectionTitle>
    <Paragraph position="0"> When human reads normal sentences, we rarely feel something is wrong with the structure we are constructing and are seldom compelled to backtrack for reconstructing an alternative. If we could simulate the internal mechanism that makes it possible to select deterministically the unique syntactic structure in a simple way, we may be able to construct more natural and efficient language processing systems. In this paper, we focus our attention on syntax of natural languages, particularly English, and predictions or expectations that can be made solely with syntactic information during the sentence recognition process are analyzed in detail. It includes machine executable mechanisms that enable proper handling of analyzed aspects and a description method of the mechanisms as grammar rules. The recognition method can be seen as a deterministic one \[2\] if we permit looking some words ahead. Also included in this paper are results of an experimental analysis in which more than seventy percent of sentences are recognized. null An analyzer which gives special attention to predictions was once developed by Kuno \[1\]. The analyzer makes use of the simple stack mechanism whose behavior is specified by rules described in Greibach normal form. In the method, however, we can find several kinds of rules that do not correspond to human predictive recognition process, which will be pointed out in this paper.</Paragraph>
    <Paragraph position="1"> The following discussion is based mainly on the author's (subjective) retrospect of the recognition process of English sentences. The author's mother tongue is Japanese and he has been learning English as a second language. It seems to the author that he can understand better how he recognizes English than how he recognizes Japanese since he has been learning English consciously and can observe rather objectively the process of recognition.</Paragraph>
    <Paragraph position="2"> The rest of this paper is organized as follows. In the next section, we discuss aspects of predictions, laying stress upon their proper handling by computers. The following section presents the results of an experiment. The conclusions are presented in the last section.</Paragraph>
  </Section>
class="xml-element"></Paper>