[FEAT] Configuring Melt but still with bugs.

parsing/NgramsExtractors/FrenchNgramsExtractor.py

 from .NgramsExtractor import NgramsExtractor
-from ..Taggers import TreeTagger
+from ..Taggers import TreeTagger, MeltTagger
 
 
 class FrenchNgramsExtractor(NgramsExtractor):
 
     def start(self):
-        self.tagger = TreeTagger()
-        # self.tagger = MeltTagger(language='fr')
+        #self.tagger = TreeTagger()
+        self.tagger = MeltTagger(language='fr')

parsing/NgramsExtractors/NgramsExtractor.py

@@ -14,22 +14,22 @@ class NgramsExtractor:
         self._label = "NP"
         self._rule = self._label + ": " + rule
         self._grammar = nltk.RegexpParser(self._rule)
-        
+
     def __del__(self):
         self.stop()
-        
+
     def start(self):
         self.tagger = TurboTagger()
-        
+
     def stop(self):
         pass
-        
-    
+
+
     """Extracts a list of ngrams.
     Returns a list of the ngrams found in the given text.
     """
     def extract_ngrams(self, contents):
-        tagged_ngrams = self.tagger.tag_text(contents)
+        tagged_ngrams = list(self.tagger.tag_text(contents))
         if len(tagged_ngrams):
             grammar_parsed = self._grammar.parse(tagged_ngrams)
             for subtree in grammar_parsed.subtrees():

parsing/NgramsExtractors/__init__.py

 from .FrenchNgramsExtractor import FrenchNgramsExtractor
-from .TurboNgramsExtractor import TurboNgramsExtractor as EnglishNgramsExtractor
-# from .EnglishNgramsExtractor import EnglishNgramsExtractor
+#from .TurboNgramsExtractor import TurboNgramsExtractor as EnglishNgramsExtractor
+from .EnglishNgramsExtractor import EnglishNgramsExtractor
 from .NgramsExtractor import NgramsExtractor