COLING 2020main2 citations
Neural Language Modeling for Named Entity Recognition
Zhihong Lei, Weiyue Wang, Christian Dugast, Hermann Ney
Abstract
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.
BibTeX
@inproceedings{lei-etal-2020-neural,
title = "Neural Language Modeling for Named Entity Recognition",
author = "Lei, Zhihong and
Wang, Weiyue and
Dugast, Christian and
Ney, Hermann",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.612/",
doi = "10.18653/v1/2020.coling-main.612",
pages = "6937--6941"
}