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 __init__(
      self,
      stopwords_file="models/FoxStoplist.txt",
      word_tokenize=None,
      sent_tokenize=None,
  ):
      self._stopwords_pattern = self.build_patterns(
          self.load_stopwords(stopwords_file)
      )
      self._sent_tokenize = (
          sent_tokenize if sent_tokenize else nltk.sent_tokenize
      )
      self._word_tokenize = (
          word_tokenize if word_tokenize else nltk.word_tokenize
      )
  
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 1 to create a new RAKE object  with example: obj = RAKE(stopwords_file, word_tokenize, sent_tokenize)