@InProceedings{mirza-EtAl:2017:Short,
  author    = {Mirza, Paramita  and  Razniewski, Simon  and  Darari, Fariz  and  Weikum, Gerhard},
  title     = {Cardinal Virtues: Extracting Relation Cardinalities from Text},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {347--351},
  abstract  = {Information extraction (IE) from text has largely focused on relations between
	individual entities, such as who has won which award. However, some facts are
	never fully mentioned, and no IE method has perfect recall. Thus, it is
	beneficial to also tap contents about the cardinalities of these relations, for
	example, how many awards someone has won. We introduce this novel problem of
	extracting cardinalities and discusses the specific challenges that set it
	apart from standard IE. We present a distant supervision method using
	conditional random fields. A preliminary evaluation results in precision
	between 3% and 55%, depending on the difficulty of relations.},
  url       = {http://aclweb.org/anthology/P17-2055}
}