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<Paper uid="P98-1061">
  <Title>A structure-sharing parser for lexicalized grammars</Title>
  <Section position="8" start_page="376" end_page="377" type="concl">
    <SectionTitle>
6 Discussion
</SectionTitle>
    <Paragraph position="0"> The approach described here offers empirical rather than formal improvements in performance. In the worst case, none of the trees  in the grammar share any structure so no optimisation is possible. However, in the typical case, there is scope for substantial structure sharing among closely related trees. Carroll et al. (1998) report preliminary results using this technique on a wide-coverage DTG (a variant of LTAG) grammar. Table 1 gives statistics for three common verbs in the grammar: the total number of trees, the size of the merged automaton (before any optimisation has occurred) and the size of the minimised automaton. The final column gives the average of the number of trees that share each state in the automaton.</Paragraph>
    <Paragraph position="1"> These figures show substantial optimisation is possible, both in the space requirements of the grammar and in the sharing of processing state between trees during parsing.</Paragraph>
    <Paragraph position="2"> As mentioned earlier, the algorithms we have presented assume that elementary trees have one anchor and one spine. Some trees, however, have secondary anchors (for example, a subcategorised preposition). One possible way of including such cases would be to construct automata from secondary anchors up the secondary spine to the main spine. The automata for both the primary and secondary anchors associated with a lexical item could then be merged, minimized and used for parsing as above.</Paragraph>
    <Paragraph position="3"> Using automata for parsing has a long history dating back to transition networks (Woods, 1970). More recent uses include Alshawi (1996) and Eisner (1997). These approaches differ from the present paper in their use of automata as part of the grammar formalism itself. Here, automata are used purely as a stepping-stone to parser optimisation: we make no linguistic claims about them. Indeed one view of this work is that it frees the linguistic descriptions from overt computational considerations. This work has perhaps more in common with the technology of LR parsing as a parser optimisation technique, and it would be interesting to compare our approach with a direct application of LR ideas to LTAGs.</Paragraph>
  </Section>
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