@InProceedings{li-EtAl:2018:K18-2,
  author    = {Li, Zuchao  and  He, Shexia  and  Zhang, Zhuosheng  and  Zhao, Hai},
  title     = {Joint Learning of {POS} and Dependencies for Multilingual Universal Dependency Parsing},
  booktitle = {Proceedings of the {CoNLL} 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies},
  month     = {October},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {65--73},
  abstract  = {This paper describes the system of team LeisureX in the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Our system predicts the part-of-speech tag and dependency tree jointly. For the basic tasks, including tokenization, lemmatization and morphology prediction, we employ the official baseline model (UDPipe). To train the low-resource languages, we adopt a sampling method based on other richresource languages. Our system achieves a macro-average of 68.31% LAS F1 score, with an improvement of 2.51% compared with the UDPipe.},
  url       = {http://www.aclweb.org/anthology/K18-2006}
}