Evaluating MateCat Translation of Performative Verbs in Legal Texts Into Arabic: The UN Charter as a Corpus

Many studies have highlighted the possibilities and limitations of using translation technology tools in the professional context. An ever-increasing body of literature also explored the use of these technologies to translate specialized texts, raising many issues, particularly the disparities between the human and automated translation of specialized discourse. To further investigate this problem, this study discusses the quality of Machine Translation of legal texts. It assesses MateCat's output of performative acts within legal texts from English to Arabic. Furthermore, it highlights the importance of using Translation Technology to work on specialized texts and how these tools help maintain consistency. For the sake of this paper, the researchers adopted the UN Charter and its official translation as a corpus, comparing it with the 'MateCat' output. Results of data analysis revealed that the MateCat translation tool can handle complex performative structures effectively and produces translations with appropriate context. However, the nature of legal text still necessitates human intervention, whether light or deep postediting, regardless of the tool used in the translation process.