Many web sites contain large sets of pages generated using a common template or layout. For example, Amazon lays out the author, title, comments, etc. in the same way in all its book pages. The values used to generate the pages (e.g., the author, title,...) typically come from a database. In this paper, we study the problem of automatically extracting the database values from the web pages without any learning examples or other similar human input. We formally define the notion of a template, and propose a model that describes how values are encoded into pages using a template. We present an extraction algorithm that uses sets of words that have similar occurrence pattern in the input pages, to construct the template. The constructed template is then used to extract values from the pages. We show experimentally that the extracted values make semantic sense in most cases.