Linguistically Informed Statistical Models of Constituent Structure for Ordering in Sentence Realization

We present several statistical models of syntactic constituent order for sentence realization. We compare several models, including simple joint models inspired by existing statistical parsing models, and several novel conditional models. The conditional models leverage a large set of linguistic features without manual feature selection. We apply and evaluate the models in sentence realization for French and German and find that a particular conditional model outperforms all others. We employ a version of that model in an evaluation on unordered trees from the Penn TreeBank. We offer this result on standard data as a reference-point for evaluations of ordering in sentence realization.