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.
Original language | English |
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Pages (from-to) | 519-525 |
Number of pages | 7 |
Journal | Journal of Beijing Institute of Technology (English Edition) |
Volume | 24 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Dec 2015 |
Keywords
- Conditional random field
- Phrase structure grammar
- Syntactic parsing
- Syntactic tree