@InProceedings{camachocollados-EtAl:2017:SemEval,
  author    = {Camacho-Collados, Jose  and  Pilehvar, Mohammad Taher  and  Collier, Nigel  and  Navigli, Roberto},
  title     = {SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {15--26},
  abstract  = {This paper introduces a new task on Multilingual and Cross-lingual SemanticThis
	paper introduces a new task on Multilingual and Cross-lingual Semantic Word
	Similarity which measures the semantic similarity of word pairs within and
	across five languages: English, Farsi, German, Italian and Spanish. High
	quality datasets were manually curated for the five languages with high
	inter-annotator agreements (consistently in the 0.9 ballpark). These were used
	for semi-automatic construction of ten cross-lingual datasets. 17 teams
	participated in the task, submitting 24 systems in subtask 1 and 14 systems in
	subtask 2. Results show that systems that combine statistical knowledge from
	text corpora, in the form of word embeddings, and external knowledge from
	lexical resources are best performers in both subtasks. More information can be
	found on the task website: http://alt.qcri.org/semeval2017/task2/},
  url       = {http://www.aclweb.org/anthology/S17-2002}
}