15. A non-transitory computer-readable medium encoded with instruction for identifying entities of a contact associated with a character string, the instructions when executed by a processor comprise the steps of: receiving a character string; evaluating whether the character string comprises a structure associated with a first defined entity, prior to any probabilistic approximation, wherein the structure comprises at least one character other than alphanumeric characters; evaluating whether the character string is found in a look up table in response to an evaluation that the character string does not comprise the structure associated with the first defined entity; replacing all numerical digits in the character string with a corresponding digit placeholder to generate a blurred character string in response to a determination that the character string is not found in the look up table; calculating, based on the blurred character string, a posterior probability to generate a score for each of a set of defined entities; and identifying the character string as one entity of the set of defined entities having a highest score that satisfies a predetermined score threshold.
15. A non-transitory computer-readable medium encoded with instruction for identifying entities of a contact associated with a character string, the instructions when executed by a processor comprise the steps of: receiving a character string; evaluating whether the character string comprises a structure associated with a first defined entity, prior to any probabilistic approximation, wherein the structure comprises at least one character other than alphanumeric characters; evaluating whether the character string is found in a look up table in response to an evaluation that the character string does not comprise the structure associated with the first defined entity; replacing all numerical digits in the character string with a corresponding digit placeholder to generate a blurred character string in response to a determination that the character string is not found in the look up table; calculating, based on the blurred character string, a posterior probability to generate a score for each of a set of defined entities; and identifying the character string as one entity of the set of defined entities having a highest score that satisfies a predetermined score threshold. 22. The computer-readable medium of claim 15 , the step of calculating a posterior probability further comprising: evaluating a full string feature of the character string, and if an instance of a first defined entity meeting the full string feature is found in a training set, then calculating a posterior probability for all entities around the full string feature, wherein if the posterior probability is higher than a full string threshold, the character string is determined to be the first defined entity, and if not: evaluating a digit blurring feature of the character string, and if an instance of a second defined entity meeting the digit blurring feature is found in the training set, then calculate a posterior probability for all entities around the digit blurring feature, wherein if the posterior probability is higher than a digit blurring threshold, the character string is determined to be the second defined entity, and if not: calculating a posterior probability for all entities around a last word feature, wherein if the posterior probability is higher than a last word threshold, the character string is determined to be a third defined entity, and if not: calculating a posterior probability for all entities around an address line feature, wherein if the posterior probability is higher than an address line threshold, the character string is determined to be a fourth defined entity, and if not: calculating a posterior probability for all entities around a first name feature, wherein if the posterior probability is higher than a first name threshold, the character string is determined to be a fifth defined entity, and if not the character string is likely an eighth defined entity.