diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 9f4618102..52069bff8 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -47,7 +47,7 @@ jobs:
           python -m flake8 spacy --count --select=E901,E999,F821,F822,F823,W605 --show-source --statistics
       - name: cython-lint
         run: |
-          python -m pip install cython-lint -c requirements.txt
+          python -m pip install cython-lint -c requirements.txt --ignore E501,W291
           cython-lint spacy
 
   tests:
diff --git a/spacy/training/align.pyx b/spacy/training/align.pyx
index 8bd43b048..79fec73c4 100644
--- a/spacy/training/align.pyx
+++ b/spacy/training/align.pyx
@@ -37,10 +37,14 @@ def get_alignments(A: List[str], B: List[str]) -> Tuple[List[List[int]], List[Li
             b2a.append(set())
         # Process the alignment at the current position
         if A[token_idx_a] == B[token_idx_b] and \
-                (char_idx_a == 0 or \
-                    char_to_token_a[char_idx_a - 1] < token_idx_a) and \
-                (char_idx_b == 0 or \
-                    char_to_token_b[char_idx_b - 1] < token_idx_b):
+                (
+                    char_idx_a == 0 or
+                    char_to_token_a[char_idx_a - 1] < token_idx_a
+                ) and \
+                (
+                    char_idx_b == 0 or
+                    char_to_token_b[char_idx_b - 1] < token_idx_b
+                ):
             # Current tokens are identical and both character offsets are the
             # start of a token (either at the beginning of the document or the
             # previous character belongs to a different token)
diff --git a/spacy/training/example.pyx b/spacy/training/example.pyx
index 1524589fa..3f0cf5ade 100644
--- a/spacy/training/example.pyx
+++ b/spacy/training/example.pyx
@@ -1,4 +1,3 @@
-import warnings
 from collections.abc import Iterable as IterableInstance
 
 import numpy
@@ -31,9 +30,9 @@ cpdef Doc annotations_to_doc(vocab, tok_annot, doc_annot):
     attrs, array = _annot2array(vocab, tok_annot, doc_annot)
     output = Doc(vocab, words=tok_annot["ORTH"], spaces=tok_annot["SPACY"])
     if "entities" in doc_annot:
-       _add_entities_to_doc(output, doc_annot["entities"])
+        _add_entities_to_doc(output, doc_annot["entities"])
     if "spans" in doc_annot:
-       _add_spans_to_doc(output, doc_annot["spans"])
+        _add_spans_to_doc(output, doc_annot["spans"])
     if array.size:
         output = output.from_array(attrs, array)
     # links are currently added with ENT_KB_ID on the token level
@@ -161,7 +160,6 @@ cdef class Example:
                 self._y_sig = y_sig
                 return self._cached_alignment
 
-
     def _get_aligned_vectorized(self, align, gold_values):
         # Fast path for Doc attributes/fields that are predominantly a single value,
         # i.e., TAG, POS, MORPH.
@@ -204,7 +202,6 @@ cdef class Example:
 
         return output.tolist()
 
-
     def _get_aligned_non_vectorized(self, align, gold_values):
         # Slower path for fields that return multiple values (resulting
         # in ragged arrays that cannot be vectorized trivially).
@@ -221,7 +218,6 @@ cdef class Example:
 
         return output
 
-
     def get_aligned(self, field, as_string=False):
         """Return an aligned array for a token attribute."""
         align = self.alignment.x2y
@@ -330,7 +326,7 @@ cdef class Example:
             missing=None
         )
         # Now fill the tokens we can align to O.
-        O = 2 # I=1, O=2, B=3
+        O = 2 # I=1, O=2, B=3  # no-cython-lint: E741
         for i, ent_iob in enumerate(self.get_aligned("ENT_IOB")):
             if x_tags[i] is None:
                 if ent_iob == O:
@@ -340,7 +336,7 @@ cdef class Example:
         return x_ents, x_tags
 
     def get_aligned_ner(self):
-        x_ents, x_tags = self.get_aligned_ents_and_ner()
+        _x_ents, x_tags = self.get_aligned_ents_and_ner()
         return x_tags
 
     def get_matching_ents(self, check_label=True):
@@ -398,7 +394,6 @@ cdef class Example:
 
         return span_dict
 
-
     def _links_to_dict(self):
         links = {}
         for ent in self.reference.ents: