diff --git a/spacy/tests/pipeline/test_spancat.py b/spacy/tests/pipeline/test_spancat.py
index 7164dc3eb..fa3b76f30 100644
--- a/spacy/tests/pipeline/test_spancat.py
+++ b/spacy/tests/pipeline/test_spancat.py
@@ -15,6 +15,8 @@ OPS = get_current_ops()
 
 SPAN_KEY = "labeled_spans"
 
+SPANCAT_COMPONENTS = ["spancat", "spancat_exclusive"]
+
 TRAIN_DATA = [
     ("Who is Shaka Khan?", {"spans": {SPAN_KEY: [(7, 17, "PERSON")]}}),
     (
@@ -41,7 +43,7 @@ def make_examples(nlp, data=TRAIN_DATA):
     return train_examples
 
 
-@pytest.mark.parametrize("name", ["spancat", "spancat_exclusive"])
+@pytest.mark.parametrize("name", SPANCAT_COMPONENTS)
 def test_no_label(name):
     nlp = Language()
     nlp.add_pipe(name, config={"spans_key": SPAN_KEY})
@@ -49,7 +51,7 @@ def test_no_label(name):
         nlp.initialize()
 
 
-@pytest.mark.parametrize("name", ["spancat", "spancat_exclusive"])
+@pytest.mark.parametrize("name", SPANCAT_COMPONENTS)
 def test_no_resize(name):
     nlp = Language()
     spancat = nlp.add_pipe(name, config={"spans_key": SPAN_KEY})
@@ -63,7 +65,7 @@ def test_no_resize(name):
         spancat.add_label("Stuff")
 
 
-@pytest.mark.parametrize("name", ["spancat", "spancat_exclusive"])
+@pytest.mark.parametrize("name", SPANCAT_COMPONENTS)
 def test_implicit_labels(name):
     nlp = Language()
     spancat = nlp.add_pipe(name, config={"spans_key": SPAN_KEY})
@@ -73,7 +75,7 @@ def test_implicit_labels(name):
     assert spancat.labels == ("PERSON", "LOC")
 
 
-@pytest.mark.parametrize("name", ["spancat", "spancat_exclusive"])
+@pytest.mark.parametrize("name", SPANCAT_COMPONENTS)
 def test_explicit_labels(name):
     nlp = Language()
     spancat = nlp.add_pipe(name, config={"spans_key": SPAN_KEY})
@@ -375,7 +377,7 @@ def test_overfitting_IO_overlapping():
         assert set([span.label_ for span in spans2]) == {"LOC", "DOUBLE_LOC"}
 
 
-@pytest.mark.parametrize("name", ["spancat", "spancat_exclusive"])
+@pytest.mark.parametrize("name", SPANCAT_COMPONENTS)
 def test_zero_suggestions(name):
     # Test with a suggester that returns 0 suggestions
 
@@ -404,7 +406,7 @@ def test_zero_suggestions(name):
     nlp.update(train_examples, sgd=optimizer)
 
 
-@pytest.mark.parametrize("name", ["spancat", "spancat_exclusive"])
+@pytest.mark.parametrize("name", SPANCAT_COMPONENTS)
 def test_set_candidates(name):
     nlp = Language()
     spancat = nlp.add_pipe(name, config={"spans_key": SPAN_KEY})