ABSTRACT
This chapter introduces an NLP ‘chunking’ strategy, again adapted for translation as mediation. It begins looking at the trainee translator tendency to translate ‘locally’ at a word-for-word technical level rather than globally, accounting for intent and contexts. The chunking strategy helps translators and interpreters to move from a local to a more global approach. There are three main elements, which may be learnt through applying a list of procedural questions similar to those in the Meta-Model. Chunking up generalizes and is, as Baker says, the most used translation strategy. This strategy also helps identify text types, which plays a key role in translating. Chunking down helps with componential analysis for translation. Chunking laterally is the strategy for re-anchoring texts in another context of culture. The risks of not chunking in terms of exoticizing texts is also briefly discussed. A short summary of the major translation strategies is given, taking Schleiermacher’s dichotomy as a useful starting point. Extensive translation examples are given, taking the reader through the chunking strategies applied. The chapter concludes with a discussion of the Logical Level role changes that take place when the more local-oriented translator or ‘interpreter’ takes on the role of the more global-oriented mediator.
