@InProceedings{wan-EtAl:2018:K18-2,
  author    = {Wan, Hui  and  Naseem, Tahira  and  Lee, Young-Suk  and  Castelli, Vittorio  and  Ballesteros, Miguel},
  title     = {{IBM} Research at the {CoNLL} 2018 Shared Task on Multilingual 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     = {92--102},
  abstract  = {This paper presents the IBM Research AI submission to the CoNLL 2018 Shared Task on Parsing Universal Dependencies. Our system implements a new joint transition-based parser, based on the Stack-LSTM framework and the Arc-Standard algorithm, that handles tokenization, part-of-speech tagging, morphological tagging and dependency parsing in one single model. By leveraging a combination of character-based modeling of words and recursive composition of partially built linguistic structures we qualified 13th overall and 7th in low resource. We also present a new sentence segmentation neural architecture based on Stack-LSTMs that was the 4th best overall.},
  url       = {http://www.aclweb.org/anthology/K18-2009}
}