@InProceedings{yang-zhang:2018:Demos,
  author    = {Yang, Jie  and  Zhang, Yue},
  title     = {NCRF++: An Open-source Neural Sequence Labeling Toolkit},
  booktitle = {Proceedings of ACL 2018, System Demonstrations},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {74--79},
  abstract  = {This paper describes NCRF++, a toolkit for neural sequence labeling. NCRF++ is designed for quick implementation of different neural sequence labeling models with a CRF inference layer. It provides users with an inference for building the custom model structure through configuration file with flexible neural feature design and utilization. Built on PyTorch\footnote{\url{http://pytorch.org/}}, the core operations are calculated in batch, making the toolkit efficient with the acceleration of GPU. It also includes the implementations of most state-of-the-art neural sequence labeling models such as LSTM-CRF, facilitating reproducing and refinement on those methods.},
  url       = {http://www.aclweb.org/anthology/P18-4013}
}