Abstract
This paper presents a supervised learning method for the pattern acquisition for handcrafted rule-based Chinese named entity recognition systems. We automatically extracted low frequency patterns based on the predefined high-frequency patterns and manually validated the new patterns and outputs of terms. The experiments show that the number of person names extracted from the Chinese Treebank increased by 14.3% after the use of the new patterns.
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References
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© 2002 Springer-Verlag Berlin Heidelberg
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Fang, X., Sheng, H. (2002). Pattern Acquisition for Chinese Named Entity Recognition: A Supervised Learning Approach. In: Yakhno, T. (eds) Advances in Information Systems. ADVIS 2002. Lecture Notes in Computer Science, vol 2457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36077-8_16
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DOI: https://doi.org/10.1007/3-540-36077-8_16
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