code: def compare_sentences(self, str_a, str_b, language):
          
  
          sents_a = []
          sents_b = []
          ratios = []
  
          # Make the latin tokenizer
          if language == "latin":
              sent_tokenizer = TokenizeSentence('latin')
  
          # Make the greek tokenizer
          elif language == "greek":
              sent_tokenizer = TokenizeSentence('greek')
  
          # Otherwise, if language, is unsupported, throw error stating accepted Language
          # values that may be used to tokenize sentences
          else:
              print("Language for sentence tokenization not recognized. "
                    "Accepted values are 'latin' and 'greek'.")
              return
  
          # If class instance is set to stem words, do so
          if self.stem_words:
              stemmer = Stemmer()
              str_a = stemmer.stem(str_a)
              str_b = stemmer.stem(str_b)
  
          # Tokenize input strings
          sents_a = sent_tokenizer.tokenize_sentences(str_a)
          sents_b = sent_tokenizer.tokenize_sentences(str_b)
  
          # Process sentences for comparison (taking into account sanitization settings)
          sents_a = self._process_sentences(sents_a)
          sents_b = self._process_sentences(sents_b)
  
          # Build matrix of edit distance ratios
          comparisons = self._calculate_ratios(sents_a, sents_b)
  
          return comparisons
docs: Tokenize two input strings on sentence boundary and return a
          matrix of Levenshtein distance ratios.
          :param language: str (language name)
          :param string_a: str
          :param string_b: str
          :return: list [[Comparison]]