In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Ini-tially a small portion of the Penn Chinese Treebank was man-ually annotated with headword and semantic dependency re-lations. 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 algo-rithm for future research.