A General-Purpose Tagger with Convolutional Neural Networks

@inproceedings{Yu2017AGT,
  title={A General-Purpose Tagger with Convolutional Neural Networks},
  author={Xiang Yu and Agnieszka Falenska and Ngoc Thang Vu},
  booktitle={SWCN@EMNLP},
  year={2017}
}
We present a general-purpose tagger based on convolutional neural networks (CNN), used for both composing word vectors and encoding context information. The CNN tagger is robust across different tagging tasks: without task-specific tuning of hyper-parameters, it achieves state-of-theart results in part-of-speech tagging, morphological tagging and supertagging. The CNN tagger is also robust against the outof-vocabulary problem, it performs well on artificially unnormalized texts. 
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