Long-distance reordering during search for hierarchical phrase-based SMT Fabienne Braune, Anita Gojun, Alexander Fraser Long-distance reordering of syntactically divergent language pairs is a critical problem. SMT has had limited success in handling these reorderings during inference, and thus deterministic preprocessing based on reordering parse trees is used. We consider German-to-English translation using Hiero. We show how to effectively model long-distance reorderings during search. Our work is novel in that we look at reordering distances of up to 50 words, and conduct a detailed manual analysis based on a new gold standard.