Finding information about people on the Web using a search engine is difficult because there is a many-to-many mapping between person names and specific persons (i.e. referents). This paper describes a person resolution system, called WebHawk. Given a list of pages obtained by submitting a person query to a search engine, WebHawk facilitates person search in three steps: First of all, a filter removes those pages that contain no information about any person. Secondly, a cluster groups the remaining pages into different clusters, each for one specific person. To make the resulting clusters more meaningful, an extractor is used to induce query-oriented personal information from each page. Finally, a namer generates an informative description for each cluster so that users can find any specific person easily. The archi-tecture of WebHawk is presented, and the four components are discussed in detail, with a separate evaluation of each component presented where appropriate. A user study shows that WebHawk complements most existing search engines and successfully improves users’ experience of person search on the Web.