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In phrase-based statistical machine translation, the phrase-table requires a large amount of memory. We will present an efficient representation with two key properties: on-demand loading and a prefix tree structure for the source phrases. We will show that this representation scales well to large data tasks and that we are able to store hundreds of millions of phrase pairs in the phrase-table. For the large Chinese-English NIST task, the memory requirements of the phrase-table are reduced todblp:conf/naacl/ZensN07 fatcat:5cjvmzuwanbtjb4ru7dzqmwobm