@InProceedings{lee-dernoncourt-szolovits:2017:SemEval,
  author    = {Lee, Ji Young  and  Dernoncourt, Franck  and  Szolovits, Peter},
  title     = {MIT at SemEval-2017 Task 10: Relation Extraction with Convolutional Neural Networks},
  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     = {978--984},
  abstract  = {Over 50 million scholarly articles have been published: they constitute a
	unique repository of knowledge. In particular, one may infer from them
	relations between scientific concepts. Artificial neural networks have recently
	been explored for relation extraction. In this work, we continue this line of
	work and present a system based on a convolutional neural network to extract
	relations. Our model ranked first in the SemEval-2017 task 10 (ScienceIE) for
	relation extraction in scientific articles (subtask C).},
  url       = {http://www.aclweb.org/anthology/S17-2171}
}