diff --git a/spacy/tests/training/test_rehearse.py b/spacy/tests/training/test_rehearse.py
index 1bb8fac86..84c507702 100644
--- a/spacy/tests/training/test_rehearse.py
+++ b/spacy/tests/training/test_rehearse.py
@@ -7,139 +7,182 @@ from spacy.training import Example
 
 TRAIN_DATA = [
     (
-        'Who is Kofi Annan?',
+        "Who is Kofi Annan?",
         {
-            'entities': [(7, 18, 'PERSON')],
-            'tags': ['PRON', 'AUX', 'PROPN', 'PRON', 'PUNCT'],
-            'heads': [1, 1, 3, 1, 1],
-            'deps': ['attr', 'ROOT', 'compound', 'nsubj', 'punct'],
-            'morphs': ['', 'Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin', 'Number=Sing', 'Number=Sing', 'PunctType=Peri'],
-            'cats': {'question': 1.0}
-        }
-    ),
-    (
-        'Who is Steve Jobs?',
-        {
-            'entities': [(7, 17, 'PERSON')],
-            'tags': ['PRON', 'AUX', 'PROPN', 'PRON', 'PUNCT'],
-            'heads': [1, 1, 3, 1, 1],
-            'deps': ['attr', 'ROOT', 'compound', 'nsubj', 'punct'],
-            'morphs': ['', 'Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin', 'Number=Sing', 'Number=Sing', 'PunctType=Peri'],
-            'cats': {'question': 1.0}
-        }
-    ),
-    (
-        'Bob is a nice person.',
-        {
-            'entities': [(0, 3, 'PERSON')],
-            'tags': ['PROPN', 'AUX', 'DET', 'ADJ', 'NOUN', 'PUNCT'],
-            'heads': [1, 1, 4, 4, 1, 1],
-            'deps': ['nsubj', 'ROOT', 'det', 'amod', 'attr', 'punct'],
-            'morphs': ['Number=Sing', 'Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin', 'Definite=Ind|PronType=Art', 'Degree=Pos', 'Number=Sing', 'PunctType=Peri'],
-            'cats': {'statement': 1.0}
+            "entities": [(7, 18, "PERSON")],
+            "tags": ["PRON", "AUX", "PROPN", "PRON", "PUNCT"],
+            "heads": [1, 1, 3, 1, 1],
+            "deps": ["attr", "ROOT", "compound", "nsubj", "punct"],
+            "morphs": [
+                "",
+                "Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin",
+                "Number=Sing",
+                "Number=Sing",
+                "PunctType=Peri",
+            ],
+            "cats": {"question": 1.0},
         },
     ),
     (
-        'Hi Anil, how are you?',
+        "Who is Steve Jobs?",
         {
-            'entities': [(3, 7, 'PERSON')],
-            'tags': ['INTJ', 'PROPN', 'PUNCT', 'ADV', 'AUX', 'PRON', 'PUNCT'],
-            'deps': ['intj', 'npadvmod', 'punct', 'advmod', 'ROOT', 'nsubj', 'punct'],
-            'heads': [4, 0, 4, 4, 4, 4, 4],
-            'morphs': ['', 'Number=Sing', 'PunctType=Comm', '', 'Mood=Ind|Tense=Pres|VerbForm=Fin', 'Case=Nom|Person=2|PronType=Prs', 'PunctType=Peri'],
-            'cats': {'greeting': 1.0, 'question': 1.0}
-        }
+            "entities": [(7, 17, "PERSON")],
+            "tags": ["PRON", "AUX", "PROPN", "PRON", "PUNCT"],
+            "heads": [1, 1, 3, 1, 1],
+            "deps": ["attr", "ROOT", "compound", "nsubj", "punct"],
+            "morphs": [
+                "",
+                "Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin",
+                "Number=Sing",
+                "Number=Sing",
+                "PunctType=Peri",
+            ],
+            "cats": {"question": 1.0},
+        },
     ),
     (
-        'I like London and Berlin.',
+        "Bob is a nice person.",
         {
-            'entities': [(7, 13, 'LOC'), (18, 24, 'LOC')],
-            'tags': ['PROPN', 'VERB', 'PROPN', 'CCONJ', 'PROPN', 'PUNCT'],
-            'deps': ['nsubj', 'ROOT', 'dobj', 'cc', 'conj', 'punct'],
-            'heads': [1, 1, 1, 2, 2, 1],
-            'morphs': ['Case=Nom|Number=Sing|Person=1|PronType=Prs', 'Tense=Pres|VerbForm=Fin', 'Number=Sing', 'ConjType=Cmp', 'Number=Sing', 'PunctType=Peri'],
-            'cats': {'statement': 1.0}
-        }
-    )
+            "entities": [(0, 3, "PERSON")],
+            "tags": ["PROPN", "AUX", "DET", "ADJ", "NOUN", "PUNCT"],
+            "heads": [1, 1, 4, 4, 1, 1],
+            "deps": ["nsubj", "ROOT", "det", "amod", "attr", "punct"],
+            "morphs": [
+                "Number=Sing",
+                "Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin",
+                "Definite=Ind|PronType=Art",
+                "Degree=Pos",
+                "Number=Sing",
+                "PunctType=Peri",
+            ],
+            "cats": {"statement": 1.0},
+        },
+    ),
+    (
+        "Hi Anil, how are you?",
+        {
+            "entities": [(3, 7, "PERSON")],
+            "tags": ["INTJ", "PROPN", "PUNCT", "ADV", "AUX", "PRON", "PUNCT"],
+            "deps": ["intj", "npadvmod", "punct", "advmod", "ROOT", "nsubj", "punct"],
+            "heads": [4, 0, 4, 4, 4, 4, 4],
+            "morphs": [
+                "",
+                "Number=Sing",
+                "PunctType=Comm",
+                "",
+                "Mood=Ind|Tense=Pres|VerbForm=Fin",
+                "Case=Nom|Person=2|PronType=Prs",
+                "PunctType=Peri",
+            ],
+            "cats": {"greeting": 1.0, "question": 1.0},
+        },
+    ),
+    (
+        "I like London and Berlin.",
+        {
+            "entities": [(7, 13, "LOC"), (18, 24, "LOC")],
+            "tags": ["PROPN", "VERB", "PROPN", "CCONJ", "PROPN", "PUNCT"],
+            "deps": ["nsubj", "ROOT", "dobj", "cc", "conj", "punct"],
+            "heads": [1, 1, 1, 2, 2, 1],
+            "morphs": [
+                "Case=Nom|Number=Sing|Person=1|PronType=Prs",
+                "Tense=Pres|VerbForm=Fin",
+                "Number=Sing",
+                "ConjType=Cmp",
+                "Number=Sing",
+                "PunctType=Peri",
+            ],
+            "cats": {"statement": 1.0},
+        },
+    ),
 ]
 
 REHEARSE_DATA = [
     (
-        'Hi Anil',
+        "Hi Anil",
         {
-            'entities': [(3, 7, 'PERSON')],
-            'tags': ['INTJ', 'PROPN'],
-            'deps': ['ROOT', 'npadvmod'],
-            'heads': [0, 0],
-            'morphs': ['', 'Number=Sing'],
-            'cats': {'greeting': 1.0}
-        }
+            "entities": [(3, 7, "PERSON")],
+            "tags": ["INTJ", "PROPN"],
+            "deps": ["ROOT", "npadvmod"],
+            "heads": [0, 0],
+            "morphs": ["", "Number=Sing"],
+            "cats": {"greeting": 1.0},
+        },
     ),
     (
-        'Hi Ravish, how you doing?',
+        "Hi Ravish, how you doing?",
         {
-            'entities': [(3, 9, 'PERSON')],
-            'tags': ['INTJ', 'PROPN', 'PUNCT', 'ADV', 'AUX', 'PRON', 'PUNCT'],
-            'deps': ['intj', 'ROOT', 'punct', 'advmod', 'nsubj', 'advcl', 'punct'],
-            'heads': [1, 1, 1, 5, 5, 1, 1],
-            'morphs': ['', 'VerbForm=Inf', 'PunctType=Comm', '', 'Case=Nom|Person=2|PronType=Prs', 'Aspect=Prog|Tense=Pres|VerbForm=Part', 'PunctType=Peri'],
-            'cats': {'greeting': 1.0, 'question': 1.0}
-        }
+            "entities": [(3, 9, "PERSON")],
+            "tags": ["INTJ", "PROPN", "PUNCT", "ADV", "AUX", "PRON", "PUNCT"],
+            "deps": ["intj", "ROOT", "punct", "advmod", "nsubj", "advcl", "punct"],
+            "heads": [1, 1, 1, 5, 5, 1, 1],
+            "morphs": [
+                "",
+                "VerbForm=Inf",
+                "PunctType=Comm",
+                "",
+                "Case=Nom|Person=2|PronType=Prs",
+                "Aspect=Prog|Tense=Pres|VerbForm=Part",
+                "PunctType=Peri",
+            ],
+            "cats": {"greeting": 1.0, "question": 1.0},
+        },
     ),
     # UTENSIL new label
     (
-        'Natasha bought new forks.',
+        "Natasha bought new forks.",
         {
-            'entities': [(0, 7, 'PERSON'), (19, 24, 'UTENSIL')],
-            'tags': ['PROPN', 'VERB', 'ADJ', 'NOUN', 'PUNCT'],
-            'deps': ['nsubj', 'ROOT', 'amod', 'dobj', 'punct'],
-            'heads': [1, 1, 3, 1, 1],
-            'morphs': ['Number=Sing', 'Tense=Past|VerbForm=Fin', 'Degree=Pos', 'Number=Plur', 'PunctType=Peri'],
-            'cats': {'statement': 1.0}
-        }
-    )
+            "entities": [(0, 7, "PERSON"), (19, 24, "UTENSIL")],
+            "tags": ["PROPN", "VERB", "ADJ", "NOUN", "PUNCT"],
+            "deps": ["nsubj", "ROOT", "amod", "dobj", "punct"],
+            "heads": [1, 1, 3, 1, 1],
+            "morphs": [
+                "Number=Sing",
+                "Tense=Past|VerbForm=Fin",
+                "Degree=Pos",
+                "Number=Plur",
+                "PunctType=Peri",
+            ],
+            "cats": {"statement": 1.0},
+        },
+    ),
 ]
 
 
 def _add_ner_label(ner, data):
     for _, annotations in data:
-        for ent in annotations['entities']:
+        for ent in annotations["entities"]:
             ner.add_label(ent[2])
 
 
 def _add_tagger_label(tagger, data):
     for _, annotations in data:
-        for tag in annotations['tags']:
+        for tag in annotations["tags"]:
             tagger.add_label(tag)
 
 
 def _add_parser_label(parser, data):
     for _, annotations in data:
-        for dep in annotations['deps']:
+        for dep in annotations["deps"]:
             parser.add_label(dep)
 
 
 def _add_textcat_label(textcat, data):
     for _, annotations in data:
-        for cat in annotations['cats']:
+        for cat in annotations["cats"]:
             textcat.add_label(cat)
 
 
-def _optimize(
-        nlp,
-        component: str,
-        data: List,
-        rehearse: bool
-):
+def _optimize(nlp, component: str, data: List, rehearse: bool):
     """Run either train or rehearse."""
     pipe = nlp.get_pipe(component)
-    if component == 'ner':
+    if component == "ner":
         _add_ner_label(pipe, data)
-    elif component == 'tagger':
+    elif component == "tagger":
         _add_tagger_label(pipe, data)
-    elif component == 'parser':
+    elif component == "parser":
         _add_tagger_label(pipe, data)
-    elif component == 'textcat_multilabel':
+    elif component == "textcat_multilabel":
         _add_textcat_label(pipe, data)
     else:
         raise NotImplementedError
@@ -160,7 +203,7 @@ def _optimize(
     return nlp
 
 
-@pytest.mark.parametrize("component", ['ner', 'tagger', 'parser', 'textcat_multilabel'])
+@pytest.mark.parametrize("component", ["ner", "tagger", "parser", "textcat_multilabel"])
 def test_rehearse(component):
     nlp = spacy.blank("en")
     nlp.add_pipe(component)
diff --git a/spacy/training/converters/conllu_to_docs.py b/spacy/training/converters/conllu_to_docs.py
index a4e70b01f..7052504cc 100644
--- a/spacy/training/converters/conllu_to_docs.py
+++ b/spacy/training/converters/conllu_to_docs.py
@@ -253,7 +253,9 @@ def conllu_sentence_to_doc(
         heads=heads,
     )
     if set_ents:
-        doc_x.ents = [Span(doc_x, ent.start, ent.end, label=ent.label) for ent in doc.ents]
+        doc_x.ents = [
+            Span(doc_x, ent.start, ent.end, label=ent.label) for ent in doc.ents
+        ]
 
     return doc_x