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<?xml version="1.0" standalone="yes"?> <Paper uid="P84-1073"> <Title>LR Pa rse rs For Natural Languages,</Title> <Section position="1" start_page="0" end_page="0" type="abstr"> <SectionTitle> Abstract </SectionTitle> <Paragraph position="0"> MLR, an extended LR parser, is introduced, and its application to natural language parsing is discussed.</Paragraph> <Paragraph position="1"> An LR parser is a ~;hift-reduce parser which is doterministically guided by a parsing table. A parsing table can be obtained automatically from a context-free phrase structure grammar. LR parsers cannot manage antl)iguous grammars such as natural language grammars, because their I)arsing tables would have multiply-defined entries, which precludes deterministic parsing. MLR, however, can handle mulliply-defined entries, using a dynamic programnting method. When an input sentence is ambiguous, the MI.R parser produces all possible parse trees witftoul parsing any part of the input sentenc:e more than once in the same way, despite the fact that the parser does not maintain a chart as in chart par~ing. Our method also prnvkles an elegant solution to the problem of multi-part-of-speech words such as &quot;that&quot;. The MLR parser and its parsing table generator have been implemented at Carnegie-Mellon University.</Paragraph> </Section> class="xml-element"></Paper>