Dependency Based Chinese Sentence Realization

This paper describes log-linear models for a general-purpose sentence realizer based on dependency structures. Unlike traditional realizers using grammar rules, our method realizes sentences by linearizing dependency relations directly in two steps. First, the relative order between head and each dependent is determined by their dependency relation. Then the best linearizations compatible with the relative order are selected by log-linear models. The log-linear models incorporate three types of feature functions, including dependency relations, surface words and headwords. Our approach to sentence realization provides simplicity, efficiency and competitive accuracy. Trained on 8,975 dependency structures of a Chinese Dependency Treebank, the realizer achieves a BLEU score of 0.8874.