In the classic bootstrap learning scheme (Riloff and Jones, 1999; Agichtein and Gravano, 2000;<cite> Bunescu and Mooney, 2007)</cite> , a small number of seed instances are used to extract new patterns from a large corpus, which are then used to extract more instances.