Fast Chinese syntactic parsing method based on conditional random fields |
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Authors: | HAN Lei LUO Sen-lin CHEN Qian-rou PAN Li-min |
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Affiliation: | School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China |
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Abstract: | A fast method for phrase structure grammar analysis is proposed based on conditional random fields (CRF). The method trains several CRF classifiers for recognizing the phrase nodes at different levels, and uses the bottom-up to connect the recognized phrase nodes to construct the syntactic tree. On the basis of Beijing forest studio Chinese tagged corpus, two experiments are designed to select the training parameters and verify the validity of the method. The result shows that the method costs 78.98.ms and 4.63.ms to train and test a Chinese sentence of 17.9 words. The method is a new way to parse the phrase structure grammar for Chinese, and has good generalization ability and fast speed. |
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Keywords: | phrase structure grammar syntactic tree syntactic parsing conditional random field |
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