Rich mark-up can considerably benefit the process of establishing bitext correspondences, that is, the task of providing correct identification and alignment methods for text segments that are translation equivalences of each other in a parallel corpus. We present a sentence alignment algorithm that, by taking advantage of previously annotated texts, obtains accuracy rates close to 100%. The algorithm evaluates the similarity of the linguistic and extralinguistic mark-up in both sides of a bitext. .
