Publication at Faculty of Mathematics and Physics |
2011
Abstract
This paper presents a work in progress on the task of unsupervised parsing, following the main stream approach of optimizing the overall probability of the corpus. We evaluate a sequence of experiments for Czech with various modifications of corpus initiation, of dependency edge probability model and of sampling procedure, stressing especially the treeness constraint.
The best configuration is then applied to 19 languages from CoNLL-2006 and CoNLL-2007 shared tasks. Our best achieved results are comparable to the state of the art in dependency parsing and outperform the previously published results for many languages.