diff --git a/strpython/pipeline.py b/strpython/pipeline.py
index a25a66aadadd0bc64e3b795632111a9731a34ee1..640ca80d00fcdec74037f2b82061434a3226ec2d 100644
--- a/strpython/pipeline.py
+++ b/strpython/pipeline.py
@@ -41,7 +41,7 @@ class Pipeline(object):
         """
         self.lang=lang[:2]
         self.ner = kwargs["ner"] if "ner" in kwargs else Spacy(lang=lang[:2])
-        self.disambiguator=kwargs["disambiguator"] if "disambiguator" in kwargs else MostCommonDisambiguator()
+        self.disambiguator=kwargs["disambiguator"] if "disambiguator" in kwargs else WikipediaDisambiguator()
 
         self.corpus_name = kwargs["corpus_name"] if "corpus_name" in kwargs else "no_name"
         self.no_name = False
@@ -52,7 +52,7 @@ class Pipeline(object):
 
         self.verbose = kwargs.get("verbose",False)
 
-    def parse(self,text,debug=False):
+    def parse(self,text,debug=False,stop_words=[]):
         """
 
         :param text:
@@ -65,7 +65,7 @@ class Pipeline(object):
         # Disambiguation
         se_identified = self.disambiguator.disambiguate(self.lang,ner_output=output)
         for top_, id in list(se_identified.items()):
-            if not id.startswith("GD"):
+            if not id.startswith("GD") or top_.lower() in stop_words:
                 del se_identified[top_]
         if debug:
             print(se_identified)
@@ -124,6 +124,8 @@ class Pipeline(object):
 
     def pipe_build(self,texts, cpu_count=cpu_count(), **kwargs):
         # Extract Spatial entities
+
+        stop_words = kwargs.get("stop_words",[])
         text_and_spatial_entities = [self.parse(text) for text in tqdm(texts,desc="Extract spatial entities from the texts", disable=(not self.verbose))]
 
         # Filter Output