This paper presents an identification framework for extracting Tibetan base noun phrase (NP). The framework includes two phases. In the first phase, Chinese base NPs are extracted from all Chinese sentences in the sentence aligned Chinese-Tibetan corpus using Stanford Chinese parser. In the second phase, the Tibetan translations of those Chinese NPs are identified using four different methods, that is, word alignment, iterative re-evaluation, dictionary and word alignment, and sequence intersection method. We implemented and tested these methods on Chinese-Tibetan sentence aligned unlabelled corpus without Tibetan POS tagger and Treebank. The experimental results demonstrate these methods can get satisfactory results, and the best performance with 0.5283 precision is got using sequence intersection identification method. The identification framework can also be extended to extract Tibetan verb phrase.