diff --git a/anansyTypes/schemas.py b/anansyTypes/schemas.py
index 0457c34..719d7b7 100644
--- a/anansyTypes/schemas.py
+++ b/anansyTypes/schemas.py
@@ -50,10 +50,10 @@ class GetSimilarWordRequest(ModifiedBaseModel):
     embedding: Embedding
 
 class GetAllPhrasesResponse(ModifiedBaseModel):
-    phrases: Optional[List[NoEmbeddingPhrase]]
+    phrases: Optional[List[Phrase]]
     
 class GetFullPhrasesRequest(ModifiedBaseModel):
-    phrases: List[NoEmbeddingPhrase]
+    phrases: List[Phrase]
 
 class GetFullPhrasesResponse(ModifiedBaseModel):
     phrases: Optional[List[Phrase]]
diff --git a/anansyTypes/structures/phrase.py b/anansyTypes/structures/phrase.py
index 4bd91a7..08f85ee 100644
--- a/anansyTypes/structures/phrase.py
+++ b/anansyTypes/structures/phrase.py
@@ -8,24 +8,24 @@ from .embedding import Embedding
 import numpy as np
 
 
-class NoEmbeddingPhrase(Lexeme):
-    def __init__(self, id: str, content: str,original_content: str):
-        #initialised with empty embedding
-        super().__init__(id=id, content=content, embedding=Embedding(data=torch.tensor([])), original_content=original_content)
+# class NoEmbeddingPhrase(Lexeme):
+#     def __init__(self, id: str, content: str,original_content: str):
+#         #initialised with empty embedding
+#         super().__init__(id=id, content=content, embedding=Embedding(data=torch.tensor([])), original_content=original_content)
 
-    @classmethod
-    def from_dict(cls, data: dict) -> "NoEmbeddingPhrase":
-        return cls(
-            id=data["id"],
-            content=data["content"],
-            original_content=data["original_content"],
-        )
-    @model_validator(mode="before")
-    @classmethod
-    def ignore_embedding(cls, values):
-        # Remove embedding from incoming data
-        values.pop("embedding", None)
-        return values
+#     @classmethod
+#     def from_dict(cls, data: dict) -> "NoEmbeddingPhrase":
+#         return cls(
+#             id=data["id"],
+#             content=data["content"],
+#             original_content=data["original_content"],
+#         )
+#     @model_validator(mode="before")
+#     @classmethod
+#     def ignore_embedding(cls, values):
+#         # Remove embedding from incoming data
+#         values.pop("embedding", None)
+#         return values
 
 class Phrase(Lexeme):
 
@@ -38,13 +38,13 @@ class Phrase(Lexeme):
             embedding=Embedding.from_dict(data["embedding"]),
         )
 
-    @classmethod
-    def from_noembeddingphrase(
-        cls, phrase: NoEmbeddingPhrase, embedding: Embedding
-    ) -> "Phrase":
-        return cls(
-            id=phrase.id,
-            content=phrase.content,
-            original_content=phrase.original_content,
-            embedding=embedding,
-        )
+    # @classmethod
+    # def from_noembeddingphrase(
+    #     cls, phrase: NoEmbeddingPhrase, embedding: Embedding
+    # ) -> "Phrase":
+    #     return cls(
+    #         id=phrase.id,
+    #         content=phrase.content,
+    #         original_content=phrase.original_content,
+    #         embedding=embedding,
+    #     )