Translating legal formulae: a corpus-driven approach
Translating legal formulae: a corpus-driven approach
Author(s): PATRIZIA GIAMPIERISubject(s): Translation Studies
Published by: Uniwersytet Adama Mickiewicza
Keywords: corpus-based translation; legal translation; legal linguistics; corpus analysis; legal language;
Summary/Abstract: Fixed lexical or syntactical expressions and formulae hallmark legal language. They serve both linguistic and legal purposes, and should be rendered accordingly in a target language and legal system. Most of the times, however, formulaic expressions are translated by resorting to calques, false cognates, or phrases that are uncommon in the target legal language (and legal system). This paper is aimed at exploring how and if corpus analysis can dispel doubts and help find acceptable translation candidates. As there are currently no publicly available legal corpora addressing corporate documents such as contracts and agreements, this paper wishes to bridge this gap by building and relying on an ad hoc corpus of authentic agreements written in English as a first language according to the laws of England and Wales. In this way, corpus evidence can help find equivalents and, possibly, address recurrent mistranslations from Italian into English. During the corpus analysis process, the paper shows and discusses search queries and how equivalents can be obtained. At the same time, it questions dictionary entries. The paper findings highlight that the consultation of the ad hoc corpus allows to find acceptable translations of Italian legal formulae and address recurrent mistranslations. English formulaic expressions, in fact, can be rendered satisfactorily thanks to the possibility of noticing word usages in context, keywords in contexts and collocations. Further research can encompass a wider variety of formulae and/or legal documents so that scholars and translators can be equipped with useful reference tools.
Journal: Comparative Legilinguistics
- Issue Year: 2022
- Issue No: 52
- Page Range: 293-317
- Page Count: 25
- Language: English