Abstract:

Most of the current CAT systems leverage Translation Memory (TM) and Termbase(TB) to enhance efficiency of translation. With respect to TM, due to its limitations in practice, whole sentence repetition often should be complemented by translation termbase, which is more flexible in use. Building a termbase requires the automatic extraction of terms, which demands knowledge of its POS (part of speech) configuration in the specific text typology. With corpus tools, we extracted n-grams of certain length and frequency from Civil Aviation Regulations in the US and examined the POS configuration of those recurrent chunks, followed by a contrast with that of literary texts. The study shows a dominance of NP and PP in recurrent chunks suitable for CAT termbase in those Civil Aviation Regulations, different from the result in literary texts.

Key words: Computer Aided Translation(CAT), termbase, n-gram, civil aviation regulations