title: Extracting keywords from documents based on a fixed list of keywords / phrases
body: <p>I have a list of approximately 100 keywords and I need to search them in a huge corpus of over 0.1 million documents. </p>
  
  <p>I don't want an exact match , for example if keyword is Growth Fund, I am expecting all the matches like growth funds, growth fund of america etc. </p>
  
  <p>Any suggestions for this? </p>
  
  <p>I have tried using spacy's PhraseMatcher but it gives an ValueError: [T001] Max length currently 10 for phrase matching.</p>
  
  <pre class="lang-py prettyprint-override"><code>import spacy
  from spacy.matcher import PhraseMatcher
  
  full_funds_list_flat = "&lt;list of 100+ Keywords&gt;"
  
  
  nlp = spacy.load('en_core_web_sm')
  keyword_patterns = [nlp(text) for text in full_funds_list_flat]
  matcher = PhraseMatcher(nlp.vocab)
  matcher.add('KEYWORD', None, *keyword_patterns)
  </code></pre>