diff --git a/spacy/tests/doc/test_span.py b/spacy/tests/doc/test_span.py
index c6890eed7..adef5922f 100644
--- a/spacy/tests/doc/test_span.py
+++ b/spacy/tests/doc/test_span.py
@@ -706,12 +706,13 @@ def test_for_partial_ent_sents():
     """Spans may be associated with multiple sentences. These .sents should always be complete, not partial, sentences,
     which this tests for.
     """
-    nlp = English()
-    text = ["Mahler's", "Symphony", "No.", "8", "was", "beautiful."]
-    doc = Doc(nlp.vocab, words=text, sent_starts=[1, 0, 0, 1, 0, 0])
+    doc = Doc(
+        English().vocab,
+        words=["Mahler's", "Symphony", "No.", "8", "was", "beautiful."],
+        sent_starts=[1, 0, 0, 1, 0, 0],
+    )
     doc.set_ents([Span(doc, 1, 4, "WORK")])
     # The specified entity is associated with both sentences in this doc, so we expect all sentences in the doc to be
     # equal to the sentences referenced in ent.sents.
     for doc_sent, ent_sent in zip(doc.sents, doc.ents[0].sents):
         assert doc_sent == ent_sent
-
diff --git a/spacy/tokens/span.pyx b/spacy/tokens/span.pyx
index 72a216e05..7750b16ed 100644
--- a/spacy/tokens/span.pyx
+++ b/spacy/tokens/span.pyx
@@ -461,7 +461,7 @@ cdef class Span:
                     if start >= self.end:
                         break
                 elif i == self.doc.length - 1:
-                    yield Span(self.doc, start, i + 1)
+                    yield Span(self.doc, start, self.doc.length)
 
     @property
     def ents(self):