parsing

Better Informed Training of Latent Syntactic Features

We study unsupervised methods for learning refinements of the nonterminals in a treebank. Following Matsuzaki et al. (2005) and Prescher (2005), we may for example split NP without supervision into NP[0] and NP[1], which behave differently. We first …

Vine Parsing and Minimum Risk Reranking for Speed and Precision

We describe our entry in the CoNLL-X shared task. The system consists of three phases: a probabilistic vine parser (Eisner and N. Smith, 2005) that produces unlabeled dependency trees, a probabilistic relation-labeling model, and a discriminative …

Final report of the 2005 language engineering workshop on statistical machine translation by parsing

Designers of SMT system have begun to experiment with tree-structured translation models. Unfortunately, SMT systems driven by such models are even more difficult to build than the already complicated WFST-based systems. The purpose of our workshop …