Described is using context information obtained from entity mentions in likely relevant documents to extract entity mentions from documents that are ambiguous with respect to their relevance to a domain. A list of entities is input into an entity extraction mechanism, which processes a large collection of documents to determine data (counts) corresponding to frequency of entity mentions. Infrequently mentioned entities are specific entities, while frequently mentioned entities are non-specific (generic or ambiguous) entities. The context surrounding mentions of the specific entities is processed to obtain interesting context terms (words, phrases or both) for the domain. The interesting context terms are then compared against the contexts of non-specific entity mentions to determine whether each non-specific entity mention is relevant to the domain. A result set containing only relevant documents or relevant mentions collection is output.