Parsing Universal Dependencies without training
Computation and Language
2017-01-13 v1
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.
Keywords
Cite
@article{arxiv.1701.03163,
title = {Parsing Universal Dependencies without training},
author = {Héctor Martínez Alonso and Željko Agić and Barbara Plank and Anders Søgaard},
journal= {arXiv preprint arXiv:1701.03163},
year = {2017}
}
Comments
EACL 2017, 8+2 pages