A General-Purpose Tagger with Convolutional Neural Networks

WS 2017  ·  Xiang Yu, Agnieszka Faleńska, Ngoc Thang Vu ·

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-the-art results in part-of-speech tagging, morphological tagging and supertagging... The CNN tagger is also robust against the out-of-vocabulary problem, it performs well on artificially unnormalized texts. read more

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