Neural Machine Translation and Contracts: A Terminological and Phraseological Analysis of DeepL's Outputs

Legal translation, among the many existing types of specialized translation, is one of those that deserve to be addressed in depth and with close attention, as it presents difficulties and particular problems, which are not encountered for other types of translation carried out in other fields. This dissertation aims to investigate and evaluate the translation of terms and phrases, identified as “rich points”, obtained as raw output from DeepL. The work is divided into five chapters, of which the first three are theoretical and will provide a general explanation in relation to legal translation, text types, Italian and English legal language and an overview on Machine Translation’s history, while the fourth and fifth will present the methodology applied to the study and the analysis of the results. With such analysis, however, no claim is made to provide an exhaustive picture of the errors or peculiarities of the rich points of the translations produced by the MT evaluated, i.e., no analysis of each output will be made, nor will all errors in the translations be described in detail.