Abstract
We present a method of improving Japanese dependency parsing by using largescalestatistical information.Our method takes into account two types of information, which have not been considered in previous statistical (machine learning based) parsing methods.One is dependency relations among case elements of a verb, and the other is cooccurrence relations between a verb and its case element.We can collect the information for these relations from the results of automatic dependencyparsing of large-scale corpora.To show the effectiveness of our method, we made an experiment of dependency parsing, where our method tries to rerank the outputs of an existing machine learning based parsing method.From the results, we found that our method can improve the accuracy of the existing method.Furthermore, we pointed out that the relation between a verb and its modifying noun in a relative clause affects dependency parsing, and integrated our relative clause analysis method with the proposed parsing method.
