14. One or more computer-readable storage media that store executable instructions to perform a method of classifying entities, the method comprising: recognizing occurrences of an entity in a plurality of documents; identifying a plurality of first features in contexts of said occurrences; assigning a label to said entity, based on weights of said first features, when probability of correctness of said label reaches a threshold, there being at least some second features in said document that are associated with said entity but that are not included among said first features; verifying correctness of said label based one or more of said second features; storing a first pair that comprise said entity and one of said first features in either a first entity-feature store that is in volatile random access memory, or a second entity feature store that is not in said memory; choosing whether to store said first pair in said first entity-feature store based on a first estimate of said frequency of said first pair in said plurality of documents; determining that said first estimate of said frequency is higher than an estimated frequency of a second pair that is stored in said first entity-feature store; and evicting said second pair from said first entity-feature store.
14. One or more computer-readable storage media that store executable instructions to perform a method of classifying entities, the method comprising: recognizing occurrences of an entity in a plurality of documents; identifying a plurality of first features in contexts of said occurrences; assigning a label to said entity, based on weights of said first features, when probability of correctness of said label reaches a threshold, there being at least some second features in said document that are associated with said entity but that are not included among said first features; verifying correctness of said label based one or more of said second features; storing a first pair that comprise said entity and one of said first features in either a first entity-feature store that is in volatile random access memory, or a second entity feature store that is not in said memory; choosing whether to store said first pair in said first entity-feature store based on a first estimate of said frequency of said first pair in said plurality of documents; determining that said first estimate of said frequency is higher than an estimated frequency of a second pair that is stored in said first entity-feature store; and evicting said second pair from said first entity-feature store. 15. The one or more computer-readable storage media of claim 14 , wherein the method further comprises: calculating said first estimate as a product of a second estimate of a frequency of said entity in said documents and a third estimate of a frequency of said feature in said documents.