The rise of the Internet has changed the face of sex trafficking. It is imperative that public and private organizations develop tools to systematically curb the growing online element of this industry. In order to do this, a framework for the indicators of sex trafficking can be built which will automate the process of sifting through online ads. This framework must be developed and constantly updated to account for an ever evolving criminal community. This study analyzed the ontology of sex trafficking in online classified ads. The study utilized text based data mining and inherent attribute information from Female Escort ads on Backpage.com. Data from fifteen California cities and counties was used to produce intelligence about California's commercial sex industry and to develop a foundational framework for automating the process to identify possible victims of sex trafficking. The framework built through this study is a successful tool to identify potential victims in online classified ads and it produced information on demographic and geographic trends in California's commercial sex industry.