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arXiv · 1701.03163

Parsing Universal Dependencies without training

Héctor Martínez Alonso·Željko Agić·Barbara Plank·Anders Søgaard
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Abstract

We propose UDP, the first training-free parser for Universal Dependencies (UD). Our algorithm is based on PageRank and a small set of head attachment rules. It features two-step decoding to guarantee that function words are attached as leaf nodes. The parser requires no training, and it is competitive with a delexicalized transfer system. UDP offers a linguistically sound unsupervised alternative to cross-lingual parsing for UD, which can be used as a baseline for such systems. The parser has very few parameters and is distinctly robust to domain change across languages.

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Héctor Martínez Alonso, Željko Agić, Barbara Plank, Anders Søgaard. 2017-01-11. Parsing Universal Dependencies without training. https://arxiv.org/abs/1701.03163

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