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Integrated Chinese Segmentation, Parsing and Named Entity Recognition
Author(s) -
Li Dongchen,
Zhang Xiantao,
Wu Xihong
Publication year - 2018
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2018.05.014
Subject(s) - parsing , computer science , segmentation , natural language processing , artificial intelligence , named entity recognition , pattern recognition (psychology) , task (project management) , management , economics
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.

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