@InProceedings{wolska-clausen:2017:BEA,
  author    = {Wolska, Magdalena  and  Clausen, Yulia},
  title     = {Simplifying metaphorical language for young readers: A corpus study on news text},
  booktitle = {Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {313--318},
  abstract  = {The paper presents first results of an ongoing project on text
	simplification focusing on linguistic metaphors. Based on an analysis
	of a parallel corpus of news text professionally simplified for
	different grade levels, we identify six types of simplification
	choices falling into two broad categories: preserving metaphors or
	dropping them. An annotation study on almost 300 source sentences with
	metaphors (grade level 12) and their simplified counterparts (grade~4)
	is conducted. The results show that most metaphors are preserved and
	when they are dropped, the semantic content tends to be preserved
	rather than dropped, however, it is reworded without metaphorical
	language. In general, some of the expected tendencies in complexity
	reduction, measured with psycholinguistic variables linked to metaphor
	comprehension, are observed, suggesting good prospect for machine
	learning-based metaphor simplification.},
  url       = {http://www.aclweb.org/anthology/W17-5035}
}