We describe the participation of the University of Amsterdam's ILPS group in the session, entity, and relevance feedback track at TREC 2010. In the Session track we investigate the use of blind relevance feedback for taking information about a previous query into account when retrieving documents for a follow-up query. In the Entity Track REF task we experiment with a window size parameter to limit the contexts that are considered by our co-occurrence model and explore the use of Freebase for type filtering, entity normalization and homepage finding. To address the ELC task we locate candidate entities based on objects shared with the example entities and rank candidates based on the predicates and objects they share with the example entities. In the relevance feedback track we evaluate a novel model that uses wikipedia as a pivot language for estimating query models.