diff --git a/sdks/python/apache_beam/transforms/util.py b/sdks/python/apache_beam/transforms/util.py
index 1d7572bebaf1..14ed2ad559bc 100644
--- a/sdks/python/apache_beam/transforms/util.py
+++ b/sdks/python/apache_beam/transforms/util.py
@@ -111,24 +111,28 @@ class CoGroupByKey(PTransform):
                     'tag2': ... ,
                     ... })
 
+  where `[]` refers to an iterable, not a list.
+
   For example, given::
 
       {'tag1': pc1, 'tag2': pc2, 333: pc3}
 
   where::
 
-      pc1 = [(k1, v1)]
-      pc2 = []
-      pc3 = [(k1, v31), (k1, v32), (k2, v33)]
+      pc1 = beam.Create([(k1, v1)]))
+      pc2 = beam.Create([])
+      pc3 = beam.Create([(k1, v31), (k1, v32), (k2, v33)])
 
-  The output PCollection would be::
+  The output PCollection would consist of items::
 
       [(k1, {'tag1': [v1], 'tag2': [], 333: [v31, v32]}),
        (k2, {'tag1': [], 'tag2': [], 333: [v33]})]
 
+  where `[]` refers to an iterable, not a list.
+
   CoGroupByKey also works for tuples, lists, or other flat iterables of
   PCollections, in which case the values of the resulting PCollections
-  will be tuples whose nth value is the list of values from the nth
+  will be tuples whose nth value is the iterable of values from the nth
   PCollection---conceptually, the "tags" are the indices into the input.
   Thus, for this input::
 
@@ -139,6 +143,8 @@ class CoGroupByKey(PTransform):
       [(k1, ([v1], [], [v31, v32]),
        (k2, ([], [], [v33]))]
 
+  where, again, `[]` refers to an iterable, not a list.
+
   Attributes:
     **kwargs: Accepts a single named argument "pipeline", which specifies the
       pipeline that "owns" this PTransform. Ordinarily CoGroupByKey can obtain