Applied Linguistics (Yuyan Wenzi Yingyong)

Abstract

One of the most important characteristics of FrameNet is that it provides a systematic description of the situation which we draw on when we try to understand the words or try to make inferences in sentences. It also demonstrates the ways in which the semantic roles are realized in syntactic structures. It provides much finer and more systematic description of semantic roles than Case Grammar, hence better meets the needs of information procsssing. The paper proposes that Chinese FrameNet be established in line with the underlying structure of English FrameNet. The paper also discusses the prospects and methods in which Chinese FrameNet is applied to information processing, and suggests that, apart from machine learning technique, the semantic features of frame elements be utilized as a plausible way to automatically identify and assign semantic role tags to the arguments of predicators in sentences.

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