A Chinese sentence segmentation approach based on comma

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Abstract

Chinese sentence segmentation is considered to be a very fundamental step in natural language processing. A successful solution for sentence boundary detection is a key step in the subsequent NLP tasks, such as parsing and machine translation, etc. In this paper, we consider comma as a sign-of-the-sentence boundary, and then divide it into two major types, i.e., the true (EOS) and the pseudo (Non-EOS). Finally, a system framework of Chinese sentence segmentation based on two-layer classifiers is presented and implemented. The experimental results on Chinese Treebank 6.0. Results show that our model achieve the F-measure of 90.7% overall, which improves by 1.5%. © 2013 Springer-Verlag.

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Xu, S., Kong, F., Li, P., & Zhu, Q. (2013). A Chinese sentence segmentation approach based on comma. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7717 LNAI, pp. 809–817). https://doi.org/10.1007/978-3-642-36337-5_82

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