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Most information in the world exists in the format of text, such as news articles and web pages. Different lines of research have been conducted to discover, understand and access knowledge about real-world entities and relations from text. However, the application of these word oriented methods to ontology integration tasks has not been yet explored. In this paper, we apply these word oriented methods to ontology integration tasks in which we analyze a noun phrase (NP) to identify its head noun, which is useful to avoid wrong relations between entities. We also propose a collaborative acquisition algorithm that combines WordNet-based and Text corpus.