 In this way the statistical distribution and use of person names in general can be analyzed instead of looking at the distributions of "Ted" and "Erica" individually.A problem that the class based model solves is that the probability of a given name in a specific language will not affect the assigned probability of a translation.A study by Stanford on improving this area of translation gives the examples that different probabilities will be assigned to "David is going for a walk" and "Ankit is going for a walk" for English as a target language due to the different number of occurrences for each name in the training data.