Two statistical parsing models applied to the Chinese Treebank

Abstract

This paper presents the first-ever results of applying statistical parsing models to the newly-available Chinese Treebank. We have employed two models, one extracted and adapted from BBN's SIFT System (Miller et al., 1998) and a TAG-based parsing model, adapted from (Chiang, 2000). On sentences with ≤40 words, the former model performs at 69% precision, 75% recall, and the latter at 77% precision and 78% recall.