Paper: Multi-Lingual Dependency Parsing At NAIST

ACL ID W06-2927
Title Multi-Lingual Dependency Parsing At NAIST
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2006
Authors

In this paper, we present a framework for multi-lingual dependency parsing. Our bottom-up deterministic parser adopts Nivre’s algorithm (Nivre, 2004) with a preprocessor. Support Vector Machines (SVMs) are utilized to determine the word dependency attachments. Then, a maxi- mum entropy method (MaxEnt) is used for determining the label of the depend- ency relation. To improve the perform- ance of the parser, we construct a tagger based on SVMs to find neighboring at- tachment as a preprocessor. Experimental evaluation shows that the proposed exten- sion improves the parsing accuracy of our base parser in 9 languages. (Hajič et al. , 2004; Simov et al. , 2005; Simov and Osenova, 2003; Chen et al. , 2003; Böh- mová et al. , 2003; Kromann, 2003; van der Beek et al. , 2002; Brants et al. ,...