diff --git a/examples/training/train_tagger.py b/examples/training/train_tagger.py
index 0673d06d2..db0627270 100644
--- a/examples/training/train_tagger.py
+++ b/examples/training/train_tagger.py
@@ -31,7 +31,7 @@ TAG_MAP = {"N": {"pos": "NOUN"}, "V": {"pos": "VERB"}, "J": {"pos": "ADJ"}}
 # strings are unicode and that the number of tags assigned matches spaCy's
 # tokenization. If not, you can always add a 'words' key to the annotations
 # that specifies the gold-standard tokenization, e.g.:
-# ("Eatblueham", {'words': ['Eat', 'blue', 'ham'] 'tags': ['V', 'J', 'N']})
+# ("Eatblueham", {'words': ['Eat', 'blue', 'ham'], 'tags': ['V', 'J', 'N']})
 TRAIN_DATA = [
     ("I like green eggs", {"tags": ["N", "V", "J", "N"]}),
     ("Eat blue ham", {"tags": ["V", "J", "N"]}),