This paper describes the application of artificial intelligence methods for the automatic extraction of translation equivalences from bilingual parallel text. In an attempt to implement as language independent a method as possible, the application's methodology features statistical inductive techniques coupled with symbolic processing techniques catering for the analysis of specific language phenomena. The method presupposes parallel texts and identifies translational equivalences at the word or multiword unit level for those cases that such an equivalence holds true. Parallel texts are first aligned at the sentence level and grammatically analyzed. Noun phrase grammars extract noun phrases, and statistical evaluation yields the most coherent multiword units on either side . Translation candidates of word or multiword units are evaluated by a similarity metric defined by the co-occurrence frequency and independent frequencies of the units . The method has been tested on an English - Greek corpus consisting of texts relevant to software systems, yielding 94% accurate translations .