Statistical Machine Translation (SMT) is a new paradigm in machine translation, which enables high-quality translation. However, many translation errors occur in the translation of complex and compound sentences because of the lack of grammatical knowledge about the global structure of a sentence. We adopt the pre-editing method, which divides sentences into clauses, and translate these clauses using the Moses SMT engine. The translation accuracy, BLEU, was 29.33%, so pre-editing has a small effect. Translation quality is degraded because the order of words is changed by not using information about other clauses. We also performed an experiment to confirm the optimum distortion-limit parameter of Moses. The Maximum BLEU was 29.45 for an English-Japanese patent translation when the distortion limit was 20 instead of -1.