Dependency Model using Posterior Context

We describe a new model for dependency structure analysis. This model learns the relationship between two phrasal units called bunsetsus as three categories; 'between', 'dependent' , and 'beyond', and estimates the dependency likelihood by considering not only the relationship between two bunsetsus but also the relationship between the left bunsetsu and a:}l of the bunsetsus to its right. We implemented this model based on the maximum entropy model. When using the Kyoto University corpus, the dependency accuracy of our model was 88%, which is about 1 % higher than that of the conventional model using exactly the same features.