17. The apparatus of claim 16 , wherein the probabilistic scoring is learned from a plurality of training sets of input strings.
16. An apparatus for extracting contact data from quotes, wherein a plurality of contacts are stored in a multi-tenant database, the apparatus comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: obtain and store a data string having a plurality of tokens in content of a search result from a search for quoted material associated with a contact; extract a sequence of tokens corresponding to the data string; recognize a first set of tokens in the sequence of tokens as a first entity based on entity recognition probabilistic scoring derived from a machine evaluation of a training set of entities; recognize a second set of tokens in the sequence of tokens as a second entity based on identifying the first entity as a first node in a tree-like structure and identifying the second entity as by a second node in the tree-like structure, the first node connected to the second node by an arc representing a probability that the first entity is followed by the second entity in a probable entity sequence, the first node connected to another node by another arc representing another probability that the first entity is followed by another entity in another probable entity sequence, the tree-like structure created by a machine evaluation of a training set of input strings; align one or more tokens of the first set of tokens as one of a plurality of probable entities using the probabilistic scoring of the first set of tokens and grammatical rules; assign the aligned one or more tokens to one entity field of corresponding predefined entity fields of the contact based on the probabilistic scoring and the linguistic cues of the probable secondary entities; and create and store a new record for the contact if none exists, or updating an existing record for the contact, using the assigned aligned one or more tokens.