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This paper proposes an ontology learning system model based on the Web search engine and Protege-OWL API, which emphasizes iterative learning approach by the extracted instances. We discuss taxonomic and non-taxonomic relationship learning separately in ontology learning system, and investigate the importance of verb plus noun phrase learning for extraction of activity concepts in Chinese. We also propose an algorithm of relevance measurement for extracting relation instances by binary keywords based on co-occurrence statistics. Finally, we build a practical system of ontology learning through learning relation instances of the Chinese festival ontology, and test the effectiveness of our method.