Abstract
Head splitting techniques have been successfully exploited to improve the asymptotic runtime of parsing algorithms for projective dependency trees, under the arc-factored model. In this article we extend these techniques to a class of non-projective dependency trees, called well-nested dependency trees with block-degree at most 2, which has been previously investigated in the literature. We define a structural property that allows head splitting for these trees, and present two algorithms that improve over the runtime of existing algorithms at no significant loss in coverage.
Highlights
Much of the recent work on dependency parsing has been aimed at finding a good balance between accuracy and efficiency
Following Pitler et al (2012), we report in Table 1 figures for the training sets of six languages used in the CoNLL-X shared task on dependency parsing (Buchholz and Marsi, 2006)
In this article we have extended head splitting techniques, originally developed for parsing of projective dependency trees, to two subclasses of well-nested dependency trees with block-degree at most 2
Summary
Much of the recent work on dependency parsing has been aimed at finding a good balance between accuracy and efficiency. While non-projective parsing under an arc-factored model can be done in time O.n2/ (McDonald et al, 2005), parsing with more informed models is intractable (McDonald and Satta, 2007) This has led several authors to investigate ‘mildly non-projective’ classes of trees, with the goal of achieving a balance between expressiveness and complexity (Kuhlmann and Nivre, 2006). We show that restricting the class of head-split trees by imposing the already mentioned 1-inherit property does not cause any additional loss in coverage, and that parsing for the combined class is possible in time O.n5/, one order of magnitude faster than the algorithm by Pitler et al (2012) for the 1-inherit class without the head-split condition.
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