diff --git a/spacy/tests/doc/test_array.py b/spacy/tests/doc/test_array.py
index c334cc6eb..7b179d662 100644
--- a/spacy/tests/doc/test_array.py
+++ b/spacy/tests/doc/test_array.py
@@ -123,14 +123,14 @@ def test_doc_from_array_heads_in_bounds(en_vocab):
 
     # head before start
     arr = doc.to_array(["HEAD"])
-    arr[0] = -1
+    arr[0] = numpy.array(-1).astype(numpy.uint64)
     doc_from_array = Doc(en_vocab, words=words)
     with pytest.raises(ValueError):
         doc_from_array.from_array(["HEAD"], arr)
 
     # head after end
     arr = doc.to_array(["HEAD"])
-    arr[0] = 5
+    arr[0] = numpy.array(5).astype(numpy.uint64)
     doc_from_array = Doc(en_vocab, words=words)
     with pytest.raises(ValueError):
         doc_from_array.from_array(["HEAD"], arr)
diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx
index f2621292c..aedb088de 100644
--- a/spacy/tokens/doc.pyx
+++ b/spacy/tokens/doc.pyx
@@ -361,9 +361,9 @@ cdef class Doc:
                     if annot is heads or annot is sent_starts or annot is ent_iobs:
                         for i in range(len(words)):
                             if attrs.ndim == 1:
-                                attrs[i] = annot[i]
+                                attrs[i] = numpy.array(annot[i]).astype(numpy.uint64)
                             else:
-                                attrs[i, j] = annot[i]
+                                attrs[i, j] = numpy.array(annot[i]).astype(numpy.uint64)
                     elif annot is morphs:
                         for i in range(len(words)):
                             morph_key = vocab.morphology.add(morphs[i])
@@ -981,7 +981,7 @@ cdef class Doc:
         for i in range(self.length):
             token = &self.c[i]
             for j in range(nr_attr):
-                c_output[i*nr_attr + j] = get_token_attr(token, c_attr_ids[j])
+                c_output[i*nr_attr + j] = numpy.array(get_token_attr(token, c_attr_ids[j])).astype(numpy.uint64)
         # Handle 1d case
         return output if len(attr_ids) >= 2 else output.reshape((self.length,))
 
@@ -1559,7 +1559,7 @@ cdef class Doc:
             for j, (attr, annot) in enumerate(token_annotations.items()):
                 if attr is HEAD:
                     for i in range(len(words)):
-                        array[i, j] = annot[i]
+                        array[i, j] = numpy.array(annot[i]).astype(numpy.uint64)
                 elif attr is MORPH:
                     for i in range(len(words)):
                         array[i, j] = self.vocab.morphology.add(annot[i])
diff --git a/spacy/tokens/span.pyx b/spacy/tokens/span.pyx
index c3495f497..1b3759128 100644
--- a/spacy/tokens/span.pyx
+++ b/spacy/tokens/span.pyx
@@ -299,7 +299,7 @@ cdef class Span:
                     for ancestor in ancestors:
                         ancestor_i = ancestor.i - self.c.start
                         if ancestor_i in range(length):
-                            array[i, head_col] = ancestor_i - i
+                            array[i, head_col] = numpy.array(ancestor_i - i).astype(numpy.uint64)
 
                 # if there is no appropriate ancestor, define a new artificial root
                 value = array[i, head_col]
@@ -307,7 +307,7 @@ cdef class Span:
                     new_root = old_to_new_root.get(ancestor_i, None)
                     if new_root is not None:
                         # take the same artificial root as a previous token from the same sentence
-                        array[i, head_col] = new_root - i
+                        array[i, head_col] = numpy.array(new_root - i).astype(numpy.uint64)
                     else:
                         # set this token as the new artificial root
                         array[i, head_col] = 0
diff --git a/spacy/training/example.pyx b/spacy/training/example.pyx
index dfd337b9e..7be363cef 100644
--- a/spacy/training/example.pyx
+++ b/spacy/training/example.pyx
@@ -443,26 +443,27 @@ def _annot2array(vocab, tok_annot, doc_annot):
         if key not in IDS:
             raise ValueError(Errors.E974.format(obj="token", key=key))
         elif key in ["ORTH", "SPACY"]:
-            pass
+            continue
         elif key == "HEAD":
             attrs.append(key)
-            values.append([h-i if h is not None else 0 for i, h in enumerate(value)])
+            row = [h-i if h is not None else 0 for i, h in enumerate(value)]
         elif key == "DEP":
             attrs.append(key)
-            values.append([vocab.strings.add(h) if h is not None else MISSING_DEP for h in value])
+            row = [vocab.strings.add(h) if h is not None else MISSING_DEP for h in value]
         elif key == "SENT_START":
             attrs.append(key)
-            values.append([to_ternary_int(v) for v in value])
+            row = [to_ternary_int(v) for v in value]
         elif key == "MORPH":
             attrs.append(key)
-            values.append([vocab.morphology.add(v) for v in value])
+            row = [vocab.morphology.add(v) for v in value]
         else:
             attrs.append(key)
             if not all(isinstance(v, str) for v in value):
                 types = set([type(v) for v in value])
                 raise TypeError(Errors.E969.format(field=key, types=types)) from None
-            values.append([vocab.strings.add(v) for v in value])
-    array = numpy.asarray(values, dtype="uint64")
+            row = [vocab.strings.add(v) for v in value]
+        values.append([numpy.array(v).astype(numpy.uint64) for v in row])
+    array = numpy.array(values, dtype=numpy.uint64)
     return attrs, array.T