diff --git a/spacy/pipeline/entity_linker.py b/spacy/pipeline/entity_linker.py
index e69fa618be9..ac05cb840bd 100644
--- a/spacy/pipeline/entity_linker.py
+++ b/spacy/pipeline/entity_linker.py
@@ -26,6 +26,8 @@
 
 ActivationsT = Dict[str, Union[List[Ragged], List[str]]]
 
+KNOWLEDGE_BASE_IDS = "kb_ids"
+
 # See #9050
 BACKWARD_OVERWRITE = True
 
@@ -426,7 +428,7 @@ def predict(self, docs: Iterable[Doc]) -> ActivationsT:
         docs_ents: List[Ragged] = []
         docs_scores: List[Ragged] = []
         if not docs:
-            return {"kb_ids": final_kb_ids, "ents": docs_ents, "scores": docs_scores}
+            return {KNOWLEDGE_BASE_IDS: final_kb_ids, "ents": docs_ents, "scores": docs_scores}
         if isinstance(docs, Doc):
             docs = [docs]
         for doc in docs:
@@ -532,7 +534,7 @@ def predict(self, docs: Iterable[Doc]) -> ActivationsT:
                 method="predict", msg="result variables not of equal length"
             )
             raise RuntimeError(err)
-        return {"kb_ids": final_kb_ids, "ents": docs_ents, "scores": docs_scores}
+        return {KNOWLEDGE_BASE_IDS: final_kb_ids, "ents": docs_ents, "scores": docs_scores}
 
     def set_annotations(self, docs: Iterable[Doc], activations: ActivationsT) -> None:
         """Modify a batch of documents, using pre-computed scores.
@@ -543,7 +545,7 @@ def set_annotations(self, docs: Iterable[Doc], activations: ActivationsT) -> Non
 
         DOCS: https://spacy.io/api/entitylinker#set_annotations
         """
-        kb_ids = cast(List[str], activations["kb_ids"])
+        kb_ids = cast(List[str], activations[KNOWLEDGE_BASE_IDS])
         count_ents = len([ent for doc in docs for ent in doc.ents])
         if count_ents != len(kb_ids):
             raise ValueError(Errors.E148.format(ents=count_ents, ids=len(kb_ids)))
@@ -553,7 +555,7 @@ def set_annotations(self, docs: Iterable[Doc], activations: ActivationsT) -> Non
             if self.save_activations:
                 doc.activations[self.name] = {}
                 for act_name, acts in activations.items():
-                    if act_name != "kb_ids":
+                    if act_name != KNOWLEDGE_BASE_IDS:
                         # We only copy activations that are Ragged.
                         doc.activations[self.name][act_name] = cast(Ragged, acts[j])