@InProceedings{ballesteros-carreras:2017:IWPT,
  author    = {Ballesteros, Miguel  and  Carreras, Xavier},
  title     = {Arc-Standard Spinal Parsing with Stack-LSTMs},
  booktitle = {Proceedings of the 15th International Conference on Parsing Technologies},
  month     = {September},
  year      = {2017},
  address   = {Pisa, Italy},
  publisher = {Association for Computational Linguistics},
  pages     = {115--121},
  abstract  = {We present a neural transition-based parser for spinal trees, a dependency
	representation of
	constituent trees. The parser uses Stack-LSTMs that compose constituent nodes
	with
	dependency-based derivations. In experiments, we show that this model adapts to
	different
	styles of dependency relations, but this choice has little effect for
	predicting constituent
	structure, suggesting that LSTMs induce useful states by themselves.},
  url       = {http://www.aclweb.org/anthology/W17-6316}
}