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Efficient EUD Parsing

Computation and Language 2020-06-02 v1
Authors: Mathieu Dehouck , Mark Anderson , Carlos Gómez-Rodríguez
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Abstract

We present the system submission from the FASTPARSE team for the EUD Shared Task at IWPT 2020. We engaged with the task by focusing on efficiency. For this we considered training costs and inference efficiency. Our models are a combination of distilled neural dependency parsers and a rule-based system that projects UD trees into EUD graphs. We obtained an average ELAS of 74.04 for our official submission, ranking 4th overall.

Cite

@article{arxiv.2006.00838,
  title  = {Efficient EUD Parsing},
  author = {Mathieu Dehouck and Mark Anderson and Carlos Gómez-Rodríguez},
  journal= {arXiv preprint arXiv:2006.00838},
  year   = {2020}
}

Comments

To published in the proceedings of the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies

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