diff --git a/recon/loaders.py b/recon/loaders.py
index f3ca606..a957e84 100644
--- a/recon/loaders.py
+++ b/recon/loaders.py
@@ -8,7 +8,7 @@
 import spacy
 import srsly
 from spacy.language import Language
-from spacy.tokens import Doc, DocBin
+from spacy.tokens import Doc, DocBin, Span as SpacySpan
 from spacy.util import get_words_and_spaces
 
 from recon.types import Example, Span, Token
@@ -120,9 +120,10 @@ def to_spacy(
             tokens = [token.text for token in example.tokens]
             words, spaces = get_words_and_spaces(tokens, example.text)
             doc = Doc(nlp.vocab, words=words, spaces=spaces)
-            doc.set_ents(
-                [doc.char_span(s.start, s.end, label=s.label) for s in example.spans]
-            )
+            spacy_spans = [
+                doc.char_span(s.start, s.end, label=s.label) for s in example.spans
+            ]
+            doc.set_ents(cast(List[SpacySpan], spacy_spans))
             doc_bin.add(doc)
     doc_bin.to_disk(path)
     return doc_bin
diff --git a/recon/types.py b/recon/types.py
index 8318f4c..11a1fb6 100644
--- a/recon/types.py
+++ b/recon/types.py
@@ -13,12 +13,13 @@
     Protocol,
     Tuple,
     Union,
+    cast,
 )
 from typing_extensions import ParamSpec
 
 from pydantic import BaseModel, field_validator, model_validator
 from spacy import displacy
-from spacy.tokens import Doc
+from spacy.tokens import Doc, Span as SpacySpan
 from spacy.util import get_words_and_spaces
 from spacy.vocab import Vocab
 from wasabi import color
@@ -130,7 +131,9 @@ def doc(self) -> Doc:
         tokens = [token.text for token in self.tokens]
         words, spaces = get_words_and_spaces(tokens, self.text)
         doc = Doc(Vocab(), words=words, spaces=spaces)
-        doc.set_ents([doc.char_span(s.start, s.end, label=s.label) for s in self.spans])
+        spans = [doc.char_span(s.start, s.end, label=s.label) for s in self.spans]
+
+        doc.set_ents(cast(List[SpacySpan], spans))
         return doc
 
     def show(
@@ -369,9 +372,10 @@ def show(self, label_suffix: str = "PRED"):
         tokens = [token.text for token in combined.tokens]
         words, spaces = get_words_and_spaces(tokens, combined.text)
         doc = Doc(Vocab(), words=words, spaces=spaces)
-        doc.spans["ref"] = [
+        ref_spans = [
             doc.char_span(s.start, s.end, label=s.label) for s in combined.spans
         ]
+        doc.spans["ref"] = cast(List[SpacySpan], ref_spans)
         displacy.render(doc, style="span", jupyter=True, options={"spans_key": "ref"})