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<Paper uid="P84-1073">
  <Title>LR Pa rse rs For Natural Languages,</Title>
  <Section position="6" start_page="355" end_page="355" type="concl">
    <SectionTitle>
6 Concluding Remarks
</SectionTitle>
    <Paragraph position="0"> The MLR parser and its parsing table generator have been implemented at Computer Science Department, Carnegie.Mellon University. The system is written in MACLISP and running on Tops-20.</Paragraph>
    <Paragraph position="1"> One good feature of an MLR parser (and of an LR parser) is that, even if the parser is to run on a small computer, the construction of the parsing table can be done on more powerful, larger computers. Once a parsing table is constructed, the execution time for parsing depends weakly on the number of productions or symbols in a grammar. Also, in spite of pseudo. parallelism, our MLR parsing is theoretically still deterministic. This is because the number of processes in our pseudo.</Paragraph>
    <Paragraph position="2"> parallelism never exceeds the number of states in the parsing table.</Paragraph>
    <Paragraph position="3"> One concern of our parser is whether the size of a parsing table remains tractable as the size of a grammar grows. Fig. 6 shows the relationship between the complexity of a grammar and its LR parsing table (excerpt from Inoue \[9\]).</Paragraph>
    <Paragraph position="4">  Fig. 6 Although the example grammars above are for programming langauges, it seems that the size of a parsing table grows only in proportion to the size of its grammar and does not grow rapidly. Therefore, there is a hope that our MLR parsers can manage grammars with thousands of phrase structure rules, which would be generated by rule-schema and meta-rules for natural language in systems such as GPSG \[7\].</Paragraph>
  </Section>
class="xml-element"></Paper>