@InProceedings{wisniewski-lacroix-yvon:2018:N18-2,
  author    = {Wisniewski, Guillaume  and  Lacroix, Ophélie  and  Yvon, François},
  title     = {Automatically Selecting the Best Dependency Annotation Design with Dynamic Oracles},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {401--406},
  abstract  = {This work introduces a new strategy to compare the numerous conventions that have been proposed over the years for expressing dependency structures and discover the one for which a parser will achieve the highest parsing performance. Instead of associating each sentence in the training set with a single gold reference we propose to consider a set of references encoding alternative syntactic representations. Training a parser with a dynamic oracle will then automatically select among all alternatives the reference that will be predicted with the highest accuracy. Experiments on the UD corpora show the validity of this approach.},
  url       = {http://www.aclweb.org/anthology/N18-2064}
}