1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct.
1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct. 30. The method as in claim 1 , selecting the at least two translation components by applying a maximum entropy model to each substring that is to be translated by the at least two translation components.