Probabilistic Parsing for German Using Sister-Head Dependencies

@inproceedings{Dubey2003ProbabilisticPF,
  title={Probabilistic Parsing for German Using Sister-Head Dependencies},
  author={Amit Dubey and Frank Keller},
  booktitle={ACL},
  year={2003}
}
We present a probabilistic parsing model for German trained on the Negra treebank. We observe that existing lexicalized parsing models using head-head dependencies, while successful for English, fail to outperform an unlexicalized baseline model for German. Learning curves show that this effect is not due to lack of training data. We propose an alternative model that uses sister-head dependencies instead of head-head dependencies. This model outperforms the baseline, achieving a labeled… CONTINUE READING
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References

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Showing 1-10 of 15 references

A stochastic topological parser of German

  • Becker, Markus, Anette Frank.
  • InProceedings of the 19th International…
  • 2002

Evaluation of the Gramotron parser for German

  • Beil, Franz, Detlef Prescher, Helmut Schmid, Sabine Schulte im Walde.
  • In
  • 2002
2 Excerpts

LoPar: Design and implementation

  • Schmid, Helmut.
  • Ms., Institute for Computational Linguistics…
  • 2000

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