%0 Conference Proceedings %T L1-L2 Parallel Dependency Treebank as Learner Corpus %A Lee, John %A Li, Keying %A Leung, Herman %Y Miyao, Yusuke %Y Sagae, Kenji %S Proceedings of the 15th International Conference on Parsing Technologies %D 2017 %8 September %I Association for Computational Linguistics %C Pisa, Italy %F lee-etal-2017-l1 %X 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. %U https://aclanthology.org/W17-6306 %P 44-49