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EACL
2006
ACL Anthology

Online Learning of Approximate Dependency Parsing Algorithms

9 years 4 months ago
Online Learning of Approximate Dependency Parsing Algorithms
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow dependency structures with multiple parents per word. We show that those extensions can make the MST framework computationally intractable, but that the intractability can be circumvented with new approximate parsing algorithms. We conclude with experiments showing that discriminative online learning using those approximate algorithms achieves the best reported parsing accuracy for Czech and Danish.
Ryan T. McDonald, Fernando C. N. Pereira
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where EACL
Authors Ryan T. McDonald, Fernando C. N. Pereira
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