Integrated Chinese Segmentation, Parsing and Named Entity Recognition

被引:1
|
作者
Li Dongchen [1 ]
Zhang Xiantao
Wu Xihong
机构
[1] Peking Univ, Key Lab Machine Percept, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
Parsing; Joint representation; Named entity recognition;
D O I
10.1049/cje.2018.05.014
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Segmentation, named entity recognition and parsing are standalone techniques in natural language processing community, and their annotations are inconsistent. However, the joint output is needed in some practical use, and they rely on the result of each other to make more concise output. A unified model is learned to resolve these three tasks simultaneously. At the training stage, the joint annotation of the three tasks are employed to learn a unified model. At the decoding stage, the three tasks are carried out on a given text to provide a consistent output. Experiment results demonstrate the higher performance for each task and verify the benefits of the unified framework.
引用
收藏
页码:756 / 760
页数:5
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