title: Stanford NLP - NER - Train NER with names that have multiple tokens
body: <p>I have recently started taking a look at Stanford NLP (using the C# port). 
  I have planned on using NER to identify store location names and product names - to do this i will need to train the tagger, which i am in the process of doing. </p>
  
  <p>However, some locations for example "Kings Cross" should only really be considered a location when both tokens are together. i.e i wouldn't want "Kings" getting tagged as a location when it is used by itself in a sentence.</p>
  
  <p>So my question really is: Is there a defined way that it is recommended that I deal with locations/names that have a space in them (both in my training files, and in code)?</p>
  
  <p>Thank you for any help. </p>