Our submission is a non-structural Example-Based Machine Translation system that translates text from Arabic to English, using a parallel corpus aligned at the paragraph / sentence level. Each new input sentence is fragmented into phrases and those phrases are matched to example patterns, using various levels of morphological information. Source-language synonyms were derived automatically and used to help locate potential translation examples for fragments of a given input sentence. We participated in the BTEC task for translating Arabic sentences to English.