Annotated training data (e.g., sentences) in a first language are used to generate annotated training data for a second language. For example, annotated sentences in English are manually collected first, and then is used to generate annotated sentences in Chinese. The annotated training data includes slot labels, slot values and carrier phrases. The carrier phrases are the portions of the training data that is outside of a slot. The carrier phrases are translated from the first language to one or more translations in the second language. The translations may include machine translations as well as human translations. Entities for the slot values are determined for the translated sentences using content sources that include locale-dependent entities. The determined entities are used to fill the slots in the translations of the second language. All or a portion of the resulting sentences may be used for training models in the second language.