Description
Summary:International audience In this paper, we present a freely available corpus of automatic translations accompanied with post-edited versions, annotated with labelsidentifying the different kinds of errors made by the MT system. These data have been extracted from translation students exercises thathave been corrected by a senior professor. This corpus can be useful for training quality estimation tools and for analyzing the types oferrors made MT system.