A Data-Driven Dependency Parser for Romanian

Abstract

We present the first data-driven dependency parser for Romanian, which has been developed using the MaltParser system and trained and evaluated on a dependency treebank for Romanian developed within the RORIC-LING project. The parser achieves a labeled attachment score of 88.6% (unlabeled 92.0%) when evaluated on held-out data from the treebank. We present a partial error analysis, focusing on accuracy for different parts of speech and dependencies of different length.