Abstract
This paper presents a Conditional Random Field (CRF) method of identifying prepositional phrases (PP) in Chinese patent documents. By using the CRF model, the identification process can be recognized as sequence labelling issue. After analyzing the characteristics of PP chunks in large scale corpus, we design several essential and helpful features and feature templates for recognizing PP chunks, and then use a CRF toolkit to train the model to identify PPs. At last, some experiments are conducted to justify the effects of the model, both the precision and recall rates are over 92%, higher than the baseline, indicating the method is reasonable and effective.
Cite
CITATION STYLE
Li, H., & Jin, Y. (2015). A CRF method of identifying prepositional phrases in Chinese patent texts. In Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015 (pp. 86–90). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-3115
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