1. A method of automatically identifying a natural language that is likely to be the predominant language of a sample text, the method including: (A) using text data defining the sample text and probability data for each of a set of natural languages to automatically obtain, for each of at least two languages in the set, sample probability data indicating a probability that the sample text would occur in the language; and (B) using the sample probability data to automatically obtain language identifying data; the language identifying data identifying the language whose sample probability data indicate the highest probability; the probability data for each of a first subset that includes one or more of the languages including N-gram probability data and the probability data for each of a second subset that includes one or more of the languages including word probability data; the N-gram probability data for each language in the first subset indicating, for each of a set of N-grams, a probability that the N-gram occurs in a text if the language is the predominant language of the text; the word probability data of each language in the second subset indicating, for each of a set of words, a probability that the word occurs in a text if the language is the predominant language of the text; in which (A) includes: (A1) automatically obtaining sample probability data for each of a third subset of the languages; for at least one language that is in the third subset and in the first subset, the sample probability data including information from the language's N-gram probability data; for at least one language that is in the third subset and in the second subset, the sample probability data including information from the language's word probability data.