@InProceedings{wang-EtAl:2017:Long6,
  author    = {Wang, Hongmin  and  Zhang, Yue  and  Chan, GuangYong Leonard  and  Yang, Jie  and  Chieu, Hai Leong},
  title     = {Universal Dependencies Parsing for Colloquial Singaporean English},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1732--1744},
  abstract  = {Singlish can be interesting to the ACL community both linguistically as a major
	creole based on English, and computationally for information extraction and
	sentiment analysis of regional social media. We investigate dependency parsing
	of Singlish by constructing a dependency treebank under the Universal
	Dependencies scheme, and then training a neural network model by integrating
	English syntactic knowledge into a state-of-the-art parser trained on the
	Singlish treebank. Results show that English knowledge can lead to 25% relative
	error reduction, resulting in a parser of 84.47% accuracies. To the best of our
	knowledge, we are the first to use neural stacking to improve cross-lingual
	dependency parsing on low-resource languages. We make both our annotation and
	parser available for further research.},
  url       = {http://aclweb.org/anthology/P17-1159}
}