One difficulty that prevents a machine from searching, retrieving and processing web content through the World Wide Web (WWW) is that most web content is presented in natural language, which cannot be processed by a machine. The current pattern-based annotation approaches can generate patterns for a given relation from unrestricted text, and they can use those generalized patterns to extract related concepts, that have the same relation, from other text. However, those approaches all have one problem unsolved: the pattern ambiguity problem. Our approach can generate lexical patterns for a particular relation from unrestricted text. Then patterns can be used to recognize concepts which have the same relation in other text. We proposed an ontology-driven pattern disambiguation process. This process can dramatically improve the performance of existing pattern-based annotation approaches.