text: Title: Is it a good idea to apply NER for translation
  Body: This may not directly related to tensor2tensor, but I am curious about to what extend NER could improve translation quality in general. Here are some examples where NER could apply.
  1. numbers, especially long digits e.g., 100,000,000. To my understand, it would be split into a serious of tokens with each element of being one digits. If it could be replaced by a special token such as _number, the length will be reduced to one.
  2. dates, for example **2 October 2018** will also be one token if converted properly. 
  
  The benefit of doing this is to shorten sentences and thus yielding a more simplified sentence structure. On the other hand, there are also bad sides. For example, it relies on a good NER system. It may also cause trouble when post-processing those NEs after translated into another language, one of which could be to retain  the orders of NEs as of in source sentences.
  
  Any comments, suggestions?