@InProceedings{santus-EtAl:2016:CogALex-V,
  author    = {Santus, Enrico  and  Gladkova, Anna  and  Evert, Stefan  and  Lenci, Alessandro},
  title     = {The CogALex-V Shared Task on the Corpus-Based Identification of Semantic Relations},
  booktitle = {Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {69--79},
  abstract  = {The shared task of the 5th Workshop on Cognitive Aspects of the Lexicon
	(CogALex-V) aims at providing a common benchmark for testing current
	corpus-based methods for the identification of lexical semantic relations
	(synonymy, antonymy, hypernymy, part-whole meronymy) and at gaining a better
	understanding of their respective strengths and weaknesses. The shared task
	uses a challenging dataset extracted from EVALution 1.0, which contains word
	pairs holding the above-mentioned relations as well as semantically unrelated
	control items (random). The task is split into two subtasks: (i) identification
	of related word pairs vs. unrelated ones; (ii) classification of the word pairs
	according to their semantic relation. This paper describes the subtasks, the
	dataset, the evaluation metrics, the seven participating systems and their
	results. The best performing system in subtask 1 is GHHH (F1 = 0.790), while
	the best system in subtask 2 is LexNet (F1 = 0.445). The dataset and the task
	description are available at
	https://sites.google.com/site/cogalex2016/home/shared-task.},
  url       = {http://aclweb.org/anthology/W16-5309}
}