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<Paper uid="C00-1017">
  <Title>Probabilistic Parsing and Psychological Plausibility</Title>
  <Section position="6" start_page="115" end_page="115" type="relat">
    <SectionTitle>
6 Related Work
</SectionTitle>
    <Paragraph position="0"> Probably mostly related to the work reported here are (Charniak et al., 1998) and (Roark and Johnson, 1999). Both report on significantly improved parsing efl:iciency by selecting only subset of edges tbr processing. There are three main differences to our at)t)roach. One is that they use a ranking fbr best-first search while we immediately prune hypotheses. They need to store a large number edges because it is not known in advance how maw of the edges will be used until a parse is found. Tile second difference is that we proceed strictly incrementally without look-ahead. (Chanfiak et al., 1998) use a non-incremental procedure, (Roark and Johnson, 1999) use a look-ahead of one word.</Paragraph>
    <Paragraph position="1"> Thirdly, we use a much simpler ranking tbnnula.</Paragraph>
    <Paragraph position="2"> Additionally, (Chanfiak et al., 1998) and (Roark and Johnson, 1999) do not use the original Penntree encoding tbr the context-fl'ee structures. Betbre training and parsing, they change/remove some of the productions and introduce new part-of-speech tags tbr auxiliaries. The exact effect of these modifications is unknown, and it is unclear if these affect compa7For the active chart, lmralellism cannot be given for different nodes types since active edges are introduced fbr right-hand side prefixes, collapsing all possible left-hand sides.</Paragraph>
    <Paragraph position="3"> rability to our results.</Paragraph>
    <Paragraph position="4"> Tile heavy restrictions in our method (immediate pruning, no look-ahead, very simple ranking formula) have consequences on the accuracy. Using right context and sorting instead of pruning yields roughly 2% higher results (compared to our base encodingS). But our work shows that even with these massive restrictions, the chart size can be reduced to 1% without a decrease in accuracy when compared to exhaustive search.</Paragraph>
  </Section>
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