Presidential Faculty Fellowship/Presidential Early Career Awards for Scientists and Engineers (PFF/PECASE)

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The project is oriented to demonstrate the use of a lexical-based parametric framework to accommodate automatic dictionary construction and to support a broad range of cross-linguistic phenomena. This effort not only provides a viable solution to resolving cross-linguistic distinctions in the context of a large-scale MT effort, capturing spatial, temporal, and aspectual knowledge, but also reduces the time for the development of large scale machine translation (MT) systems. The first task consists of determining the procedures for the automatic dictionary support for MT, with demonstration of its use to languages other than English such as Arabic and Korean. A second task consists of the extension of an existing MT model to include a broader range of different linguistic phenomena through an interlingua which accommodates the compositional derivation of spatial relations. A final task is the extension of current lexical-semantic representation to include temporal and aspectual knowledge.