Transition based neural network dependency parsing of Tibetan

In order to improve the performance of Tibetan natural language processing applications such as machine translation, sentiment analysis and other tasks, this article proposes a neural network-based method for syntactic dependence. Part corpus Qinghai Normal University’s part-of-speech tag set is marked by corresponding mapping relationship transformed into annotated national standard set. At same time, CoNLL format dependency syntax tree library constructed, shift-reduce plus network adopted systematically study analyze syntax. Thereby improving quality analysis, its accuracy rate reaches UAS:94.59%