@InProceedings{fancellu-EtAl:2017:EACLshort,
  author    = {Fancellu, Federico  and  Lopez, Adam  and  Webber, Bonnie  and  He, Hangfeng},
  title     = {Detecting negation scope is easy, except when it isn't},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {58--63},
  abstract  = {Several corpora have been annotated with negation scope---the set of words
	whose meaning is negated by a cue like the word ``not''---leading to the
	development of classifiers that detect negation scope with high accuracy. We
	show that for nearly all of these corpora, this high accuracy can be attributed
	to a single fact:  they frequently annotate negation scope as a single span of
	text delimited by punctuation. For negation scopes not of this form, detection
	accuracy is low and under-sampling the easy training examples does not
	substantially improve accuracy. We demonstrate that this is partly an artifact
	of annotation guidelines, and we argue that future negation scope annotation
	efforts should focus on these more difficult cases.},
  url       = {http://www.aclweb.org/anthology/E17-2010}
}