@InProceedings{martinezalonso-EtAl:2017:EACLlong,
  author    = {Mart\'{i}nez Alonso, H\'{e}ctor  and  Agi\'{c}, \v{Z}eljko  and  Plank, Barbara  and  S{\o}gaard, Anders},
  title     = {Parsing Universal Dependencies without training},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {230--240},
  abstract  = {We present UDP, the first training-free parser for Universal Dependencies (UD).
	Our algorithm is based on  PageRank and a small set of specific dependency head
	rules. UDP 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. The parser has very
	few parameters and distinctly robust to domain change across languages.},
  url       = {http://www.aclweb.org/anthology/E17-1022}
}