diff --git a/spacy/tests/pipeline/test_entity_linker.py b/spacy/tests/pipeline/test_entity_linker.py
index f6f6f6fd0..493cbe1fa 100644
--- a/spacy/tests/pipeline/test_entity_linker.py
+++ b/spacy/tests/pipeline/test_entity_linker.py
@@ -476,6 +476,86 @@ def test_candidate_generation(nlp):
     assert_almost_equal(adam_ent_cands[0].prior_prob, 0.9)
 
 
+def test_candidate_generation_multiple_docs(nlp):
+    """Test correct candidate generation with multiple docs."""
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
+    docs = [nlp("douglas adam Adam shrubbery"), nlp("shrubbery Adam douglas adam")]
+
+    douglas_ents = [docs[0][0:1], docs[1][2:3]]
+    adam_ents = [docs[0][1:2], docs[1][3:4]]
+    Adam_ents = [docs[0][2:3], docs[1][1:2]]
+    shrubbery_ents = [docs[0][3:4], docs[1][0:1]]
+
+    # adding entities
+    mykb.add_entity(entity="Q1", freq=27, entity_vector=[1])
+    mykb.add_entity(entity="Q2", freq=12, entity_vector=[2])
+    mykb.add_entity(entity="Q3", freq=5, entity_vector=[3])
+
+    # adding aliases
+    mykb.add_alias(alias="douglas", entities=["Q2", "Q3"], probabilities=[0.8, 0.1])
+    mykb.add_alias(alias="adam", entities=["Q2"], probabilities=[0.9])
+
+    # test the size of the relevant candidates
+    adam_ent_cands = list(
+        get_candidates_v2(
+            mykb,
+            [
+                SpanGroup(doc=docs[0], spans=[adam_ents[0]]),
+                SpanGroup(doc=docs[1], spans=[adam_ents[1]]),
+            ],
+        )
+    )
+    assert len(adam_ent_cands) == 2
+    assert (
+        len(
+            list(
+                get_candidates_v2(
+                    mykb,
+                    [
+                        SpanGroup(doc=docs[0], spans=[douglas_ents[0]]),
+                        SpanGroup(doc=docs[1], spans=[douglas_ents[1]]),
+                    ],
+                )
+            )
+        )
+        == 2
+    )
+    Adam_ent_cands = list(
+        get_candidates_v2(
+            mykb,
+            [
+                SpanGroup(doc=docs[0], spans=[Adam_ents[0]]),
+                SpanGroup(doc=docs[1], spans=[Adam_ents[1]]),
+            ],
+        )
+    )
+    assert len(Adam_ent_cands) == 2
+    assert (
+        len(Adam_ent_cands[0][0]) == 0 and len(Adam_ent_cands[1][0]) == 0
+    )  # default case sensitive
+    shrubbery_ents_cands = list(
+        get_candidates_v2(
+            mykb,
+            [
+                SpanGroup(doc=docs[0], spans=[shrubbery_ents[0]]),
+                SpanGroup(doc=docs[1], spans=[shrubbery_ents[1]]),
+            ],
+        )
+    )
+    assert len(shrubbery_ents_cands) == 2
+    assert len(shrubbery_ents_cands[0][0]) == 0 and len(shrubbery_ents_cands[1][0]) == 0
+
+    # test the content of the candidates
+    assert (
+        adam_ent_cands[0][0][0].entity_id_ == adam_ent_cands[1][0][0].entity_id_ == "Q2"
+    )
+    assert adam_ent_cands[0][0][0].alias == adam_ent_cands[1][0][0].alias == "adam"
+    assert_almost_equal(adam_ent_cands[0][0][0].entity_freq, 12)
+    assert_almost_equal(adam_ent_cands[1][0][0].entity_freq, 12)
+    assert_almost_equal(adam_ent_cands[0][0][0].prior_prob, 0.9)
+    assert_almost_equal(adam_ent_cands[1][0][0].prior_prob, 0.9)
+
+
 def test_el_pipe_configuration(nlp):
     """Test correct candidate generation as part of the EL pipe"""
     nlp.add_pipe("sentencizer")