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<Paper uid="C02-1023">
  <Title>A Chart-Parsing Algorithm for Efficient Semantic Analysis</Title>
  <Section position="3" start_page="0" end_page="0" type="ackno">
    <SectionTitle>
6 Discussion
</SectionTitle>
    <Paragraph position="0"> We have presented a new algorithm for a completely semantic parse of a sequence of symbols in a graph-based formalism. The new algorithm has a temporal complexity like in Eq. 6, to be compared to the complexity of a purely recursive algorithm, like in Eq. 5.</Paragraph>
    <Paragraph position="1"> In the worst case, the second function is still dominated by a function which grows hyperexponentially in relation to a84 : the number of possible interpretations multiplied by the time used to sum up the score of an interpretation3. In practice, the values of the parameters a72 and a158 are fairly large, so this member is still small during the first steps, but it grows very quickly.</Paragraph>
    <Paragraph position="2"> As for the other member of the function, it is hyperexponential in the case of Eq. 5, whereas it is of order a158a34a84 a10 a107a109a108  a14 , in the case of Eq. 6.</Paragraph>
    <Paragraph position="3"> Practically, to make the semantic parsing algorithm acceptable, the problem of the hyperexponential growth of the number of interpretations has to be eliminated at some point. In the system we have implemented, a threshold mechanism allows to reject, for every predicate, the unlikely assignments. This practically leaves up only a small maximum number of assignments in the assignments table, for every predicate--typically 3. This means that the number of interpretations is no longer of the or- null &amp;quot;simply&amp;quot; exponential. This implementation mechanism makes the practical computing time acceptable when running on an average computer for input sequences of no more than approximately 15 symbols. In order to give a comprehensive solution to the problem, future developments will try to develop heuristics to find out the best solutions without having to compute the whole list of all possible interpretations and sort it by decreasing value of semantic compatibility. For example, by trying to explore the search space (of all possible interpreta3Namely, null a164a130a140a123a165a143a166a31a167a82a168a169a164a171a170a90a172a27a173a15a174a71a175a55a167a148a170 . tions) from maximum values of the assignments, it may be possible to generate only the 10 or 20 best interpretations without having to score all of them to start with.</Paragraph>
  </Section>
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