diff --git a/spacy/pipeline/edit_tree_lemmatizer.py b/spacy/pipeline/edit_tree_lemmatizer.py
index a56c9975e..e83fe63ba 100644
--- a/spacy/pipeline/edit_tree_lemmatizer.py
+++ b/spacy/pipeline/edit_tree_lemmatizer.py
@@ -128,7 +128,7 @@ class EditTreeLemmatizer(TrainablePipe):
             for (predicted, gold_lemma) in zip(
                 eg.predicted, eg.get_aligned("LEMMA", as_string=True)
             ):
-                if gold_lemma is None:
+                if gold_lemma is None or gold_lemma == "":
                     label = -1
                 else:
                     tree_id = self.trees.add(predicted.text, gold_lemma)
diff --git a/spacy/tests/pipeline/test_edit_tree_lemmatizer.py b/spacy/tests/pipeline/test_edit_tree_lemmatizer.py
index b12ca5dd4..c4f9b09f3 100644
--- a/spacy/tests/pipeline/test_edit_tree_lemmatizer.py
+++ b/spacy/tests/pipeline/test_edit_tree_lemmatizer.py
@@ -139,6 +139,20 @@ def test_incomplete_data():
     assert doc[1].lemma_ == "like"
     assert doc[2].lemma_ == "blue"
 
+    # Check that incomplete annotations are ignored.
+    scores, _ = lemmatizer.model([eg.predicted for eg in train_examples], is_train=True)
+    _, dX = lemmatizer.get_loss(train_examples, scores)
+    xp = lemmatizer.model.ops.xp
+
+    # Missing annotations.
+    assert xp.count_nonzero(dX[0][0]) == 0
+    assert xp.count_nonzero(dX[0][3]) == 0
+    assert xp.count_nonzero(dX[1][0]) == 0
+    assert xp.count_nonzero(dX[1][3]) == 0
+
+    # Misaligned annotations.
+    assert xp.count_nonzero(dX[1][1]) == 0
+
 
 def test_overfitting_IO():
     nlp = English()