The first research on integrating controlled language data in an Example-Based Machine Translation (EBMT) system was published in [Gough & Way, 2003]. We improve on their sub-sentential alignment algorithm to populate the system’s databases with more than six times as many potentially useful fragments. Together with two simple novel improvements—correcting mistranslations in the lexicon, and allowing multiple translations in the lexicon—translation quality improves considerably when target language translations are constrained. We also develop the first EBMT system which attempts to filter the source language data using controlled language specifications. We provide detailed automatic and human evaluations of a number of experiments carried out to test the quality of the system. We observe that our system outperforms Logomedia in a number of tests. Finally, despite conflicting results from different automatic evaluation metrics, we observe a preference for controlling the source data rather than the target translations.