@InProceedings{adel-schutze:2017:EMNLP2017,
  author    = {Adel, Heike  and  Sch\"{u}tze, Hinrich},
  title     = {Global Normalization of Convolutional Neural Networks for Joint Entity and Relation Classification},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {1723--1729},
  abstract  = {We introduce globally normalized convolutional neural networks for joint entity
	classification and relation extraction. In particular, we propose a way to
	utilize a linear-chain conditional random field output layer for predicting
	entity types and relations between entities at the same time. Our experiments
	show that global normalization outperforms a locally normalized softmax layer
	on a benchmark dataset.},
  url       = {https://www.aclweb.org/anthology/D17-1181}
}