In this paper, we have shown a method of improving the quality of neural machine translation by translating/transliterating name entities as a preprocessing step. Through experiments we have shown the performance gain of our system. For evaluation we considered three types of name entities viz person names, location names and organization names. The system was able to correctly translate mostly all the name entities. For person names the accuracy was 99.86%, for location names the accuracy was 99.63% and for organization names the accuracy was 99.05%. Overall, the accuracy of the system was 99.52%

翻译：本文提出了一种方法，通过将命名实体翻译/音译作为预处理步骤，提升神经机器翻译的质量。通过实验，我们展示了系统的性能提升。在评估中，我们考虑了三种类型的命名实体，即人名、地名和组织名。该系统能够正确翻译几乎所有命名实体。对于人名，准确率为99.86%；对于地名，准确率为99.63%；对于组织名，准确率为99.05%。总体而言，系统的准确率为99.52%。