title: WordNetLemmatizer not returning the right lemma unless POS is explicit - Python NLTK
body: <p>I'm lemmatizing the Ted Dataset Transcript. There's something strange I notice:
  Not all words are being lemmatized. To say,</p>
  
  <pre><code>selected -&gt; select
  </code></pre>
  
  <p>Which is right. </p>
  
  <p>However, <code>involved !-&gt; involve</code> and <code>horsing !-&gt; horse</code> unless I explicitly input the 'v' (Verb) attribute.</p>
  
  <p>On the python terminal, I get the right output but not in my <a href="http://pastebin.com/midgUJ02" rel="noreferrer">code</a>:</p>
  
  <pre><code>&gt;&gt;&gt; from nltk.stem import WordNetLemmatizer
  &gt;&gt;&gt; from nltk.corpus import wordnet
  &gt;&gt;&gt; lem = WordNetLemmatizer()
  &gt;&gt;&gt; lem.lemmatize('involved','v')
  u'involve'
  &gt;&gt;&gt; lem.lemmatize('horsing','v')
  u'horse'
  </code></pre>
  
  <p>The relevant section of the code is this:</p>
  
  <pre><code>for l in LDA_Row[0].split('+'):
      w=str(l.split('*')[1])
      word=lmtzr.lemmatize(w)
      wordv=lmtzr.lemmatize(w,'v')
      print wordv, word
      # if word is not wordv:
      #   print word, wordv
  </code></pre>
  
  <p>The whole code is <a href="http://pastebin.com/midgUJ02" rel="noreferrer">here</a>. </p>
  
  <p>What is the problem?</p>