Webnox: web knowledge extraction

The paper describes and evaluates a system for extracting knowledge from the web that uses a domain independent fact extraction approach and a self supervised learning algorithm. Using a trust algorithm, the precision of the system is improved to over 70% compared with a baseline of 52%. The paper describes and evaluates a system for extracting knowledge from the web that uses a domain independent fact extraction approach and a self supervised learning algorithm. Using a trust algorithm, the precision of the system is improved to over 70% compared with a baseline of 52%. The paper describes and evaluates a system for extracting knowledge from the web that uses a domain independent fact extraction approach and a self supervised learning algorithm. Using a trust algorithm, the precision of the system is improved to over 70% compared with a baseline of 52%. The paper describes and evaluates a system for extracting knowledge from the web that uses a domain independent fact extraction approach and a self supervised learning algorithm. Using a trust algorithm, the precision of the system is improved to over 70% compared with a baseline of 52%. The paper describes and evaluates a system for extracting knowledge from the web that uses a domain independent fact extraction approach and a self supervised learning algorithm. Using a trust algorithm, the precision of the system is improved to over 70% compared with a baseline of 52%.