We investigate the effectiveness of selftraining PCFG grammars with latent annotations (PCFG-LA) for parsing languages with different amounts of labeled training data. Compared to...
We present a probabilistic parsing model for German trained on the Negra treebank. We observe that existing lexicalized parsing models using head-head dependencies, while successf...
Many program maintenance tools rely on traditional parsing techniques to obtain syntactic level models of the code being maintained. When, for some reason, code cannot be parsed, ...
Statistical parsers have become increasingly accurate, to the point where they are useful in many natural language applications. However, estimating parsing accuracy on a wide var...
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...