@InProceedings{ji-wu-lan:2017:K17-3,
  author    = {Ji, Tao  and  Wu, Yuanbin  and  Lan, Man},
  title     = {A Fast and Lightweight System for Multilingual Dependency Parsing},
  booktitle = {Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {237--242},
  abstract  = {We present a multilingual dependency parser with a bidirectional-LSTM (BiLSTM)
	feature extractor and a multi-layer perceptron (MLP) classifier. We trained our
	transition-based projective parser in UD version 2.0 datasets without any
	additional data. The parser is fast, lightweight and effective on big
	treebanks.
	In the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal
	Dependencies, the official results show that the macro-averaged LAS F1 score of
	our system Mengest is 61.33%.},
  url       = {http://www.aclweb.org/anthology/K17-3025}
}