Zhihong Lei
2020
Neural Language Modeling for Named Entity Recognition
Zhihong Lei
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Weiyue Wang
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Christian Dugast
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Hermann Ney
Proceedings of the 28th International Conference on Computational Linguistics
Named entity recognition is a key component in various natural language processing systems, and neural architectures provide significant improvements over conventional approaches. Regardless of different word embedding and hidden layer structures of the networks, a conditional random field layer is commonly used for the output. This work proposes to use a neural language model as an alternative to the conditional random field layer, which is more flexible for the size of the corpus. Experimental results show that the proposed system has a significant advantage in terms of training speed, with a marginal performance degradation.
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