@InProceedings{herbelot-kochmar:2016:COLING,
  author    = {Herbelot, Aur\'{e}lie  and  Kochmar, Ekaterina},
  title     = {‘Calling on the classical phone’: a distributional model of adjective-noun errors in learners’ English},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {976--986},
  abstract  = {In this paper we discuss three key points related to error detection (ED) in
	learners’ English. We focus on content word ED as one of the most challenging
	tasks in this area, illustrating our claims on adjective--noun (AN)
	combinations. In particular, we (1) investigate the role of con- text in
	accurately capturing semantic anomalies and implement a system based on
	distributional topic coherence, which achieves state-of-the-art accuracy on a
	standard test set; (2) thoroughly investigate our system’s performance across
	individual adjective classes, concluding that a class- dependent approach is
	beneficial to the task; (3) discuss the data size bottleneck in this area, and
	highlight the challenges of automatic error generation for content words.},
  url       = {http://aclweb.org/anthology/C16-1093}
}