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In this paper, I first make an observation that there is a certain parallelism in the scope interpretation possibilities of adverbs and quantifiers with respect to different types complex predicates in Japanese, drawing on a comparison of the light verb construction and the causative construction. I will then argue that previous approaches to complex predicates in Japanese in the lexicalist tradition (Matsumoto 1996; Manning et al. 1999) fail to capture this generalization successfully. Finally, building on a novel approach to syntax/semantics interface in HPSG by Cipollone (2001), I develop an analysis of the semantic structure of complex predicates that accounts for the empirical observation straightforwardly.
We examine how a large-scale computational grammar can account for the complex nature of Japanese verbal compounds. Previous computational Japanese grammars have tried to avoid the problem by simple solutions such as enumerating as many verbal compounds in the lexicon as possible. In contrast, we develop the analysis that is linguistically adequate and computationally tractable and thus meets the requirement of a syntactically and semantically precise natural language processing of Japanese like Bond et al. (2005). Our analysis distinguishes between two kinds of verbal compounds: syntactic compounds, which are fully productive; and lexical compounds, which are of varying productivity.
This paper proposes an annotating scheme that encodes honorifics (respectful words). Honorifics are used extensively in Japanese, reflecting the social relationship (e.g. social ranks and age) of the referents. This referential information is vital for resolving zero
pronouns and improving machine translation outputs. Annotating honorifics is a complex task that involves identifying a predicate with honorifics, assigning ranks to referents of the
predicate, calibrating the ranks, and connecting referents with their predicates.
The Deep Linguistic Processing with HPSG Initiative (DELH-IN) provides the infrastructure needed to produce open-source semantic transfer-based machine translation systems. We have made available a prototype Japanese-English machine translation system built from existing resources include parsers, generators, bidirectional grammars and a transfer engine.