diff --git a/spacy/tests/pipeline/test_span_finder.py b/spacy/tests/pipeline/test_span_finder.py
index 9777dc9f6..ebe1879d4 100644
--- a/spacy/tests/pipeline/test_span_finder.py
+++ b/spacy/tests/pipeline/test_span_finder.py
@@ -198,29 +198,17 @@ def test_span_finder_suggester():
     nlp = Language()
     docs = [nlp("This is an example."), nlp("This is the second example.")]
     docs[0].spans[SPANS_KEY] = [docs[0][3:4]]
-    docs[1].spans[SPANS_KEY] = [docs[1][3:5]]
-    span_finder = nlp.add_pipe("span_finder", config={"spans_key": SPANS_KEY})
-    nlp.initialize()
-    # Setting bias terms to 1000 to always make it predict something.
-    scorer_model = span_finder.model.get_ref("scorer")
-    bias = scorer_model.layers[0].get_param("b")
-    bias += 1000
-    scorer_model.layers[0].set_param("b", bias)
-    span_finder.set_annotations(docs, span_finder.predict(docs))
-
+    docs[1].spans[SPANS_KEY] = [docs[1][0:4], docs[1][3:5]]
     suggester = registry.misc.get("spacy.span_finder_suggester.v1")(
         spans_key=SPANS_KEY
     )
-
     candidates = suggester(docs)
-
-    span_length = 0
-    for doc in docs:
-        span_length += len(doc.spans[SPANS_KEY])
-
-    assert span_length == len(candidates.dataXd)
     assert type(candidates) == Ragged
-    assert len(candidates.dataXd[0]) == 2
+    assert len(candidates) == 2
+    assert list(candidates.dataXd[0]) == [3, 4]
+    assert list(candidates.dataXd[1]) == [0, 4]
+    assert list(candidates.dataXd[2]) == [3, 5]
+    assert list(candidates.lengths) == [1, 2]
 
 
 def test_overfitting_IO():