class_docstr: Implementation of RAKE -- Rapid Automatic Keywords Extraction From Individual Documents
  https://github.com/aneesha/RAKE/blob/master/rake.py
  
  To make a class for rake python implementation for easy incorporation in other modules.
  This class is used to extract keywords from textual document, such as description of entity from DBpedia.
class_docstr_tok: ["Implementation","of","RAKE","--","Rapid","Automatic","Keywords","Extraction","From","Individual","Documents","https",":","\/\/github.com\/aneesha\/RAKE\/blob\/master\/rake.py","To","make","a","class","for","rake","python","implementation","for","easy","incorporation","in","other","modules",".","This","class","is","used","to","extract","keywords","from","textual","document",",","such","as","description","of","entity","from","DBpedia","."]
code: def extract(self, text, ratio=3):
      phrases = self.ranking_phrases(self.candidate_phrases(text))
      phrases = Counter(phrases).most_common(
          int(len(phrases.keys()) / ratio)
      )
      phrases, _ = zip(*phrases)
      return phrases
  
imports: from sematch.utility import FileIO
  from nltk.stem import WordNetLemmatizer
  from nltk.corpus import wordnet
  import nltk
  from collections import Counter
  import itertools
  import string
  import re
label_desc: Use image node_id 6 for calling the RAKE obj's underlying member method code with example usage: obj.extract(text, ratio) and returns: phrases