As the web becomes an increasingly important source of information, tools for modeling, searching, and extracting information from Web pages are indispensable. By modeling the structure of a Web page defined by its markup tags, one can easily extract target information using structural templates. This paper introduces the Tree Template Automatic Generator (TTAG) that learns tree-structured templates from training Web pages. TTAG was applied to both query-based and frequently updated Web sites, and produced effective templates from a small number of examples. The experiments show that TTAG is a powerful extraction tool for semi-structured information sources.