Automatically Acquired Lexical Knowledge Improves Japanese Joint Morphological and Dependency Analysis
Daisuke Kawahara, Yuta Hayashibe, Hajime Morita, Sadao Kurohashi · International Workshop/Conference on Parsing Technologies · 2017
This paper presents a joint model for morphological and dependency analysis based on automatically acquired lexical knowledge. This model takes advantage of rich lexical knowledge to simultaneously resolve word segmentation, POS, and dependency ambiguities. In our experiments on Japanese, we show the effectiveness of our joint model over conventional pipeline models.