title: Conventions for making Stanford Ner CRF Training data
body: <p>I have to make a good NER CRF based model. I am targeting a vast domain and total no of classes that I am targeting are 17. I have also made a good set of features set(austen.prop) that should work for me by doing a lot of experiments. NER is not producing good results. I need to know <strong>limitations of NER</strong> which is CRF based in context of training data size etc.<br></p>
  
  <p>I searched a lot but till now I am unable to find the conventions that one should follow in making training data.<br></p>
  
  <p>(Note: I know completely how to make model and use it, I just need to know is there any conventions that some percentage of each target class should exist etc.)</p>
  
  <p>If anybody can guide me, I would be thankful to you.</p>