@InProceedings{lee-li-leung:2017:IWPT,
  author    = {Lee, John  and  Li, Keying  and  Leung, Herman},
  title     = {L1-L2 Parallel Dependency Treebank as Learner Corpus},
  booktitle = {Proceedings of the 15th International Conference on Parsing Technologies},
  month     = {September},
  year      = {2017},
  address   = {Pisa, Italy},
  publisher = {Association for Computational Linguistics},
  pages     = {44--49},
  abstract  = {This opinion paper proposes the use of parallel treebank as learner corpus.  We
	show how an L1-L2 parallel treebank --- i.e., parse trees of non-native
	sentences, aligned to the parse trees of their target hypotheses --- can
	facilitate retrieval of sentences with specific learner errors.  We argue for
	its benefits, in terms of corpus re-use and interoperability, over a
	conventional learner corpus annotated with error tags.                    As a proof
	of
	concept,
	we conduct a case study on word-order errors made by learners of Chinese as a
	foreign language.  We report precision and recall in retrieving a range of
	word-order error categories from L1-L2 tree pairs annotated in the Universal
	Dependency framework.},
  url       = {http://www.aclweb.org/anthology/W17-6306}
}