An Empirical Evaluation of Automatic Conversion from Constituency to Dependency in Hungarian

In this paper, we investigate the differences between Hungarian sentence parses based on automatically converted and manually annotated dependency trees. We also train constituency parsers on the manually annotated constituency treebank and then convert their output to dependency trees. We argue for the importance of training on gold standard corpora, and we also demonstrate that although the results obtained by training on the constituency treebank and converting the output to dependency format and those obtained by training on the automatically converted dependency treebank are similar in terms of accuracy scores, the typical errors made by different systems differ from each other.