MaltParser: A Language-Independent System for Data-Driven Dependency Parsing

  title={MaltParser: A Language-Independent System for Data-Driven Dependency Parsing},
  author={Joakim Nivre and Johan Hall and Jens Nilsson and Atanas Chanev and G{\"u}lsen Eryigit and Sandra K{\"u}bler and Svetoslav Marinov and Erwin Marsi},
  journal={Natural Language Engineering},
One of the potential advantages of data-driven approaches to natural language processing is that they can be ported to new languages, provided that the necessary linguistic data resources are available. In practice, this advantage can be hard to realize if models are overfitted to a particular language or linguistic annotation scheme. Thus, using two state-of-the-art statistical parsers developed for English to parse Italian, Corazza et al. [6] report an increase in error rate of 15–18%, and… CONTINUE READING
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