This paper presents an effective algorithm of annotation adaptation for constituency treebanks, which transforms a treebank from one annotation guideline to another with an iterative optimization procedure, thus to build a much larger treebank to train an enhanced parser without increasing model complexity. Experiments show that the transformed Tsinghua Chinese Treebank as additional training data brings significant improvement over the baseline trained on Penn Chinese Treebank only.
['Xiang Li', 'Wenbin Jiang', 'Lu Y', 'Qun Liu']
Iterative Transformation of Annotation Guidelines for Constituency Parsing