diff --git a/text_extensions_for_pandas/array/test_token_span.py b/text_extensions_for_pandas/array/test_token_span.py
index 613ebe0a..27af62d8 100644
--- a/text_extensions_for_pandas/array/test_token_span.py
+++ b/text_extensions_for_pandas/array/test_token_span.py
@@ -366,6 +366,19 @@ def test_as_frame(self):
         )
         self.assertEqual(len(df), len(arr))
 
+    def test_multi_doc(self):
+        arr1 = self._make_spans()
+
+        text2 = "Hello world."
+        tokens2 = SpanArray(text2, [0, 6], [5, 11])
+        arr2 = TokenSpanArray(tokens2, [0, 0], [1, 2])
+
+        series = pd.concat([pd.Series(arr1), pd.Series(arr2)])
+        self.assertFalse(series.array.is_single_document)
+        self.assertEqual(2, len(series.array.split_by_document()))
+        self._assertArrayEquals(arr1, series.array.split_by_document()[0])
+        self._assertArrayEquals(arr2, series.array.split_by_document()[1])
+
 
 @pytest.mark.skipif(LooseVersion(pa.__version__) < LooseVersion("2.0.0"),
                     reason="Nested dictionaries only supported in Arrow >= 2.0.0")
diff --git a/text_extensions_for_pandas/array/token_span.py b/text_extensions_for_pandas/array/token_span.py
index 062624ca..82e11668 100644
--- a/text_extensions_for_pandas/array/token_span.py
+++ b/text_extensions_for_pandas/array/token_span.py
@@ -983,20 +983,20 @@ def is_single_document(self) -> bool:
             # More than one tokenization and at least one span. Check whether
             # every span has the same text.
 
-            # Find the first text ID that is not NA
-            first_text_id = None
-            for b, t in zip(self._begins, self._text_ids):
+            # Find the first span that is not NA
+            first_target_text = None
+            for b, t in zip(self._begin_tokens, self.target_text):
                 if b != Span.NULL_OFFSET_VALUE:
-                    first_text_id = t
+                    first_target_text = t
                     break
-            if first_text_id is None:
+            if first_target_text is None:
                 # Special case: All NAs --> Zero documents
                 return True
             return not np.any(np.logical_and(
                 # Row is not null...
-                np.not_equal(self._begins, Span.NULL_OFFSET_VALUE),
+                np.not_equal(self._begin_tokens, Span.NULL_OFFSET_VALUE),
                 # ...and is over a different text than the first row's text ID
-                np.not_equal(self._text_ids, first_text_id)))
+                np.not_equal(self.target_text, first_target_text)))
 
     def split_by_document(self) -> List["SpanArray"]:
         """