Improving the Efficiency for Joint POS-Tagging and Dependency Parsing with Uptraining
Zhang Meisha · Intelligent Computer and Applications · 2014
POS tagging and dependency parsing are basic tasks of sentence-level natural language processing. Generally POS-tagging is a necessary prerequisite for dependency parsing. The joint models which link the two tasks together and process them by a unified model have achieved improved performances,because joint modeling can avoid the error-propagation problem. However,the time complexity of joint models can be always so large,thus yields much slower speed. This paper proposes a method based on uptraining technique to improve the speed of joint models,with only very little loss in performances.