1. A computer-implemented method, comprising: obtaining, at a computing device having one or more processors, (i) an aligned bi-text for a source language and a target language, and (ii) a supervised sequence model for the source language; labeling, at the computing device, a source side of the aligned bi-text using the supervised sequence model to obtain a labeled source side of the aligned bi-text; projecting, at the computing device, labels from the labeled source side to a target side of the aligned bi-text to obtain a labeled target side of the aligned bi-text; filtering, at the computing device, the labeled target side based on a task of a natural language processing (NLP) system configured to utilize a sequence model for the target language to obtain a filtered target side of the aligned bi-text; and training, at the computing device, the sequence model for the target language using posterior regularization with soft constraints on the filtered target side to obtain a trained sequence model for the target language.