A Machine Learning Approach to Determine Semantic Dependency Structure in Chinese

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Jiajun Yan, David B. Bracewell, Fuji Ren, Shingo Kuroiwa

Published: 2006, Last Modified: 05 Feb 2026FLAIRS 2006EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manually annotated with headword and semantic dependency relations. An initial investigation is then done using a Naive Bayesian Classifier and some handcrafted rules. The results show that the algorithms and proposed approach are effective at determining semantic dependency structure automatically. The Naive Bayesian Classifier makes a good baseline algorithm for future research.