Paper: Japanese Dependency Analysis Using Cascaded Chunking

ACL ID W02-2016
Title Japanese Dependency Analysis Using Cascaded Chunking
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2002

In this paper, we propose a new statistical Japanese dependency parser using a cascaded chunking model. Conventional Japanese statistical depen- dency parsers are mainly based on a probabilistic model, which is not always efficient or scalable. We propose a new method that is simple and efficient, since it parses a sentence deterministically only de- ciding whether the current segment modifies the segment on its immediate right hand side. Experi- ments using the Kyoto University Corpus show that the method outperforms previous systems as well as improves the parsing and training efficiency.