Publication at Faculty of Mathematics and Physics |
2011
Abstract
For many languages, we are not able to train any supervised parser, because there are no manually annotated data available. This problem can be solved by using a parallel corpus with English, parsing the English side, projecting the dependencies through word-alignment connections, and training a parser on the projected trees.
In this paper, we introduce a simple algorithm using a combination of various word-alignment symmetrizations. We prove that our method outperforms previous work, even though it uses McDonald's maximum-spanning-tree parser as it is, without any "unsupervised" modifications.