Sub-phrasal matching and structural templates in example-based MT

In this work I look at two different paradigms of Example-Based Machine Translation (EBMT). I combine the strengths of these two systems and build a new EBMT engine that combines sub-phrasal matching with structural templates. This synthesis results in higher translation quality and more graceful degradation, yielding 1.5% to 7.5% relative improvement in BLEU scores.