We present a novel scheme for word-based Japanese typed dependency parsing which integrates syntactic structure analysis and grammatical function analysis such as predicate-argument structure analysis. Compared to bunsetsu-based dependency parsing, which is predominantly used in Japanese NLP, it provides a natural way of extracting syntactic constituents, which is useful for downstream applications such as statistical machine translation. It also makes it possible to jointly decide dependency and predicate-argument structure, which is usually implemented as two separate steps.
By using grammatical functions as dependency labels, we achieved a better accuracy for assigning function labels than SynCha, while keeping the converted bunsetsu-based dependency accuracy as high as CaboCha, where they are ones of the state-of-the-art predicate-argument structure analyzers and dependency parsers, respectively.