Paper: A Fast Accurate Deterministic Parser For Chinese

ACL ID P06-1054
Title A Fast Accurate Deterministic Parser For Chinese
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

We present a novel classifier-based deter- ministic parser for Chinese constituency parsing. Our parser computes parse trees from bottom up in one pass, and uses classifiers to make shift-reduce decisions. Trained and evaluated on the standard training and test sets, our best model (us- ing stacked classifiers) runs in linear time and has labeled precision and recall above 88% using gold-standard part-of-speech tags, surpassing the best published re- sults. Our SVM parser is 2-13 times faster than state-of-the-art parsers, while produc- ing more accurate results. Our Maxent and DTree parsers run at speeds 40-270 times faster than state-of-the-art parsers, but with 5-6% losses in accuracy.