title: How to correct POS tagging errors?
body: <p>I currently have a text file containing a few hundred words which I am trying to pos tag in python. The file contains already tokenized words. When applying the pos tagger to these words, most are incorrectly tagged with the most frequent tags being POS or CD. I know that pos taggers are not 100% accurate but in this case, there are so many incorrect POS and CD tags being applied that I think I may need to format the input file or change something with the tagger to get the correct tags.</p>
  
  <p>As mentioned previously there are a few hundred words in the txt file so I have provided a small example of the words and format which they are in. The file is called <code>token.txt</code>:</p>
  
  <pre><code>['research', 'interests', 'member', 'language', 'computation']
  </code></pre>
  
  <p>The python code is:</p>
  
  <pre><code>import nltk
  from nltk.corpus import *
  
  f = open('token.txt')
  data=f.read().split()
  fire = nltk.pos_tag(data)
  print(fire)
  </code></pre>
  
  <p>The current result for this small sample is:</p>
  
  <pre><code>[("['research',", 'JJ'), ("'interests',", 'POS'), ("'member',", 'POS'), ("'language',", 'CD'), ("'computation']", 'NNS')]
  </code></pre>
  
  <p>I know interests should be tagged NNS and member should be tagged NN as well as language. The incorrect tagging is happening throughout the document</p>