This study attempts to determine whether a neural machine translation system that encounters repeated occurrences of a certain concept, expressed through a variety of synonyms, will consistently translate each synonym a given way or use multiple target-language synonyms as translations for each source-language synonym. The frequency with which the system recasts the meaning expressed by the source-language synonym using constructions involving different parts of speech is also considered. The study analyzes English translations generated by Google Translate for selected original French earnings releases. The translations generated by Google Translate are also compared to published English translations, where available, and the characteristics of both types of translations with respect to synonym use are compared to those of selected original English earnings releases.