http://hdl.handle.net/20.500.12084/72 Submissions dealing with lexicographic, terminological, and translation data (from Eurac Research). 2026-01-28T17:55:31Z http://hdl.handle.net/20.500.12124/60 MT@BZ translation corpus v1.0 De Camillis, Flavia; Chiocchetti, Elena; Stemle, Egon W. The MT@BZ is a translation corpus that consists of 52 decrees published by the Autonomous Province of Bolzano (South Tyrol) aligned with their machine translated versions. More precisely, it consists of 26 decrees in German and the same 26 in Italian in their official versions, respectively machine translated by the project team into Italian and into German. 10 of them are COVID-19 related decress, while 16 are miscellaneous. Overall, they consist of around 130,000 words. Their machine translation was carried out with a customized version of ModernMT. Later, the corpus was uploaded first into the annotation platform Webanno, then transferred to Inception. Four annotators annotated the translation errors made by the machine according to an ad hoc error taxonomy for quality assessment. Finally, the annotations were curated to create a gold standard corpus. 2023-06-13T00:00:00Z http://hdl.handle.net/20.500.12124/62 MT@BZ annotation guidelines v1.0 Chiocchetti, Elena; De Camillis, Flavia The MT@BZ annotation guidelines are guidelines for legal Italian-German machine translation quality assessment. Particularly, they cover the South Tyrolean German variety. They are based on version 1.3.3 of the Annotation Guidelines for English-Dutch Machine Translation Quality Assessment (https://www.lt3.ugent.be/publications/annotation-guidelines-for-english-dutch-machine-tr/). The guidelines also include specific instructions on how to annotate errors in WebAnno/INCEpTION and which sources to consult when assessing the correctness of a translation. 2022-05-31T00:00:00Z