diff --git a/orangecontrib/text/tests/test_topic_modeling.py b/orangecontrib/text/tests/test_topic_modeling.py
index 94cd906d2..16b06cff5 100644
--- a/orangecontrib/text/tests/test_topic_modeling.py
+++ b/orangecontrib/text/tests/test_topic_modeling.py
@@ -6,6 +6,7 @@
 from orangecontrib.text.topics import LdaWrapper, HdpWrapper, LsiWrapper, NmfWrapper
 from orangecontrib.text.corpus import Corpus
 from orangecontrib.text import preprocess
+from orangecontrib.text.tag import AveragedPerceptronTagger
 
 
 class BaseTests:
@@ -82,6 +83,17 @@ def test_existing_attributes(self):
         self.assertEqual(self.model.doc_topic.shape[1],
                          self.model.actual_topics)
 
+    def test_pos_tags(self):
+        corpus = Corpus.from_file('deerwester')
+        pp_list = [preprocess.WordPunctTokenizer(),
+                   AveragedPerceptronTagger(),
+                   preprocess.PosTagFilter("NN")]
+        for pp in pp_list:
+            corpus = pp(corpus)
+        self.model.fit_transform(corpus)
+        self.assertTrue(all("_NN" in word for word in
+                            self.model.get_top_words_by_id(0, 10)[0]))
+
 
 class LDATests(unittest.TestCase, BaseTests):
     def setUp(self):
diff --git a/orangecontrib/text/topics/topics.py b/orangecontrib/text/topics/topics.py
index a96162179..33314e566 100644
--- a/orangecontrib/text/topics/topics.py
+++ b/orangecontrib/text/topics/topics.py
@@ -64,6 +64,7 @@ def infer_ngrams_corpus(corpus, return_dict=False):
         (i, attribute.name) for i, attribute in enumerate(corpus.domain.attributes)
         if 'bow-feature' in attribute.attributes
     ]
+
     if len(bow_features) == 0:
         corpus = BowVectorizer().transform(corpus)
         bow_features = [
@@ -74,7 +75,8 @@ def infer_ngrams_corpus(corpus, return_dict=False):
     feature_presence = corpus.X.sum(axis=0)
     keep = [(i, a) for i, a in bow_features if feature_presence[0, i] > 0]
     # sort features by the order in the dictionary
-    dictionary = Dictionary(corpus.ngrams_iterator(include_postags=True), prune_at=None)
+    dictionary = Dictionary(corpus.ngrams_iterator(include_postags=False),
+                            prune_at=None)
     idx_of_keep = np.argsort([dictionary.token2id[a] for _, a in keep])
     keep = [keep[i][0] for i in idx_of_keep]
     result = []