diff --git a/spacy/tests/pipeline/test_coref.py b/spacy/tests/pipeline/test_coref.py
index d252cfa83..8a20e43a4 100644
--- a/spacy/tests/pipeline/test_coref.py
+++ b/spacy/tests/pipeline/test_coref.py
@@ -6,7 +6,11 @@ from spacy.training import Example
 from spacy.lang.en import English
 from spacy.tests.util import make_tempdir
 from spacy.pipeline.coref import DEFAULT_CLUSTERS_PREFIX
-from spacy.ml.models.coref_util import select_non_crossing_spans, get_candidate_mentions
+from spacy.ml.models.coref_util import (
+    select_non_crossing_spans,
+    get_candidate_mentions,
+    get_sentence_map,
+)
 
 # fmt: off
 TRAIN_DATA = [
@@ -35,6 +39,13 @@ def nlp():
     return English()
 
 
+@pytest.fixture
+def snlp():
+    en = English()
+    en.add_pipe("sentencizer")
+    return en
+
+
 def test_add_pipe(nlp):
     nlp.add_pipe("coref")
     assert nlp.pipe_names == ["coref"]
@@ -158,17 +169,21 @@ def test_crossing_spans():
     assert gold == guess
 
 
-def test_mention_generator():
-    # don't use the fixture because we want the sentencizer
-    nlp = English()
+def test_mention_generator(snlp):
+    nlp = snlp
     doc = nlp("I like text.")  # four tokens
     max_width = 20
     mentions = get_candidate_mentions(doc, max_width)
     assert len(mentions[0]) == 10
 
     # check multiple sentences
-    nlp.add_pipe("sentencizer")
     doc = nlp("I like text. This is text.")  # eight tokens, two sents
     max_width = 20
     mentions = get_candidate_mentions(doc, max_width)
     assert len(mentions[0]) == 20
+
+
+def test_sentence_map(snlp):
+    doc = snlp("I like text. This is text.")
+    sm = get_sentence_map(doc)
+    assert sm == [0, 0, 0, 0, 1, 1, 1, 1]