Privacy policy is a legal document in which the users are informed about the data practices used by the organizations. Past research indicates that the privacy policies are long, include incomplete information, and are hard to read. Research also shows that users are not inclined to read these long and verbose policies. The solution that we are proposing in this paper is to build tools that can assist users with finding relevant content in the privacy policies for their queries using semantic approach. This paper presents the development of domain ontology for privacy policies so that the relevant sentences related to privacy question can be automatically identified. For this study, we built an ontology and also validated and evaluated the ontology using qualitative and quantitative methods including competency questions, data driven, and user evaluation. Results from the evaluation of ontology depicted that the amount of text to read was significantly reduced as the users had to only read selected text that ranged from 1% to 30% of a privacy policy. The amount of content selected for reading depended on the query and its associated keywords. This finding shows that the time required to read a policy was significantly reduced as the ontology directed the user to the content related to a given user query. This finding was also confirmed by the results of the user study session. The results from the user study session indicated that the users found ontology helpful in finding relevant sentences as compared to reading the entire policy.