  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.
