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We investigate a lattice-structured LSTM model for Chinese NER, which encodes a sequence of input characters as well as all potential words that match a lexicon.
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Wanxiang Che, Mengqiu Wang, Christopher D Manning, and Ting Liu. 2013 · 2013
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Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
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Multi-prototype Chinese character embedding
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End-to-end sequence labeling via Bi-directional LSTM-CNNs-CRF
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Improving named entity recognition for Chinese social media with word segmentation representation learning
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Combining discrete and neural features for sequence labeling
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Adversarial multi-criteria learning for Chinese word segmentation
Xinchi Chen, Zhan Shi, Xipeng Qiu, and Xuanjing Huang. 2017 · 2017
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Joint segmentation and named entity recognition using dual decomposition in Chinese discharge summaries
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