Abstract

We develop a new approach to learning phrase translations from parallel corpora, and show that it performs with very high coverage and accuracy in choosing French translations of English named-entity phrases in a test corpus of software manuals. Analysis of a subset of our results suggests that the method should also perform well on more general phrase translation tasks.