diff --git a/spacy/pipeline/pipes.pyx b/spacy/pipeline/pipes.pyx
index b3fa77732..98414736b 100644
--- a/spacy/pipeline/pipes.pyx
+++ b/spacy/pipeline/pipes.pyx
@@ -1136,14 +1136,6 @@ class EntityLinker(Pipe):
         # how many neightbour sentences to take into account
         self.n_sents = cfg.get("n_sents", 0)
 
-    def set_kb(self, kb):
-        self.kb = kb
-
-    def require_model(self):
-        # Raise an error if the component's model is not initialized.
-        if getattr(self, "model", None) in (None, True, False):
-            raise ValueError(Errors.E109.format(name=self.name))
-
     def require_kb(self):
         # Raise an error if the knowledge base is not initialized.
         if len(self.kb) == 0:
diff --git a/spacy/tests/regression/test_issue5230.py b/spacy/tests/regression/test_issue5230.py
index 42b08eeff..b46bf9063 100644
--- a/spacy/tests/regression/test_issue5230.py
+++ b/spacy/tests/regression/test_issue5230.py
@@ -70,14 +70,13 @@ def tagger():
 
 def entity_linker():
     nlp = Language()
-    nlp.add_pipe(nlp.create_pipe("entity_linker"))
+    kb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    kb.add_entity("test", 0.0, zeros((1, 1), dtype="f"))
+    nlp.add_pipe(nlp.create_pipe("entity_linker", {"kb": kb}))
     entity_linker = nlp.get_pipe("entity_linker")
     # need to add model for two reasons:
     # 1. no model leads to error in serialization,
     # 2. the affected line is the one for model serialization
-    kb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
-    kb.add_entity("test", 0.0, zeros((1, 1), dtype="f"))
-    entity_linker.set_kb(kb)
     entity_linker.begin_training(pipeline=nlp.pipeline)
     return entity_linker