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EMNLP
2007

Characterizing the Errors of Data-Driven Dependency Parsing Models

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Characterizing the Errors of Data-Driven Dependency Parsing Models
We present a comparative error analysis of the two dominant approaches in datadriven dependency parsing: global, exhaustive, graph-based models, and local, greedy, transition-based models. We show that, in spite of similar performance overall, the two models produce different types of errors, in a way that can be explained by theoretical properties of the two models. This analysis leads to new directions for parser development.
Ryan T. McDonald, Joakim Nivre
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where EMNLP
Authors Ryan T. McDonald, Joakim Nivre
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