We propose a method to alleviate the problem of referential granularity for Japanese zero pronoun resolution. We use dictionary definition sentences to extract ‘representative’ arguments of predicative definition words; e.g. ‘arrest’ is likely to take police as the subject and criminal as its object. These representative arguments are far more informative than ‘person’ that is provided by other valency dictionaries. They are auto-extracted using both Shallow parsing and Deep parsing for greater quality and quantity. Initial results are highly promising, obtaining more specific information about selectional preferences. An architecture of zero pronoun resolution using these representative arguments is described.

This paper raises a neglected issue in the study of ellipsis resolution. The existence of ellipsis under certain constructions is often disguised due to the structure that assigns the nominative marking to what is typically the object. This kind of ellipsis deserves attention in view of the fact that its referent is the agent of the sentence and that these constructions are observed in diverse languages. A problem is posed by virtue of the fact that English is not one of those languages, and it overtly expresses the referent of ellipsis that is implicit in those languages that use those constructions. Hence, the recognition and resolution of such ellipses is of importance particularly in machine translation systems that translate sentences with “incognito ellipsis” from those languages into English. After presenting the types of constructions, the paper explicates the mechanisms that govern the constructions in Japanese, and proposes a method to resolve such incognito ellipses along with common ellipses in a unified manner.

Some Japanese clauses contain more than one argument ellipsis, and yet this fact has not adequately been accounted for in the study of ellipsis resolution in the current literature, which predominantly focus resolving one ellipsis per sentence. This paper proposes a method using a "salient referent list", which identifies the referents of such multiple argument ellipses as well as offers ellipsis resolution as a whole by considering contextual information.