diff --git a/tools/python_api/src_py/query_result.py b/tools/python_api/src_py/query_result.py
index 0b34342ef7..fb14ed7346 100644
--- a/tools/python_api/src_py/query_result.py
+++ b/tools/python_api/src_py/query_result.py
@@ -22,7 +22,7 @@ class QueryResult:
 
     close()
         Close the query result.
-    
+
     get_as_df()
         Get the query result as a Pandas DataFrame.
 
@@ -35,10 +35,14 @@ class QueryResult:
     get_column_names()
         Get the names of the columns in the query result.
 
+    get_as_networkx(directed=True)
+        Converts the nodes and rels in query result into a NetworkX graph representation.
+
     get_as_torch_geometric()
-        Get the query result as a PyTorch Geometric Data object.
+        Converts the nodes and rels in query result into a PyTorch Geometric graph representation
+        torch_geometric.data.Data or torch_geometric.data.HeteroData.
     """
-    
+
     def __init__(self, connection, query_result):
         """
         Parameters
@@ -200,19 +204,22 @@ def reset_iterator(self):
 
     def get_as_networkx(self, directed=True):
         """
-        Get the query result as a NetworkX graph.
+        Convert the nodes and rels in query result into a NetworkX directed or undirected graph
+        with the following rules:
+        Columns with data type other than node or rel will be ignored.
+        Duplicated nodes and rels will be converted only once.
 
         Parameters
         ----------
         directed : bool
             Whether the graph should be directed. Defaults to True.
-        
+
         Returns
         -------
         networkx.DiGraph or networkx.Graph
             Query result as a NetworkX graph.
         """
-        
+
         self.check_for_query_result_close()
         import networkx as nx
 
@@ -253,7 +260,8 @@ def encode_node_id(node, table_primary_key_dict):
             _id = node["_id"]
             node_id = node['_label'] + "_" + str(_id["offset"])
             if node['_label'] not in table_primary_key_dict:
-                props = self.connection._get_node_property_names(node['_label'])
+                props = self.connection._get_node_property_names(
+                    node['_label'])
                 for prop_name in props:
                     if props[prop_name]['is_primary_key']:
                         table_primary_key_dict[node['_label']] = prop_name
@@ -288,12 +296,43 @@ def _get_properties_to_extract(self):
 
     def get_as_torch_geometric(self):
         """
-        Get the query result as a PyTorch Geometric graph.
+        Converts the nodes and rels in query result into a PyTorch Geometric graph representation
+        torch_geometric.data.Data or torch_geometric.data.HeteroData.
+
+        For node conversion, numerical and boolean properties are directly converted into tensor and
+        stored in Data/HeteroData. For properties cannot be converted into tensor automatically 
+        (please refer to the notes below for more detail), they are returned as unconverted_properties.
+
+        For rel conversion, rel is converted into edge_index tensor director. Edge properties are returned
+        as edge_properties.
+
+        Node properties that cannot be converted into tensor automatically:
+        - If the type of a node property is not one of INT64, DOUBLE, or BOOL, it cannot be converted
+          automatically.
+        - If a node property contains a null value, it cannot be converted automatically.
+        - If a node property contains a nested list of variable length (e.g. [[1,2],[3]]), it cannot be 
+          converted automatically.
+        - If a node property is a list or nested list, but the shape is inconsistent (e.g. the list length 
+          is 6 for one node but 5 for another node), it cannot be converted automatically.
+
+        Additional conversion rules:
+        - Columns with data type other than node or rel will be ignored.
+        - Duplicated nodes and rels will be converted only once.
 
         Returns
         -------
         torch_geometric.data.Data or torch_geometric.data.HeteroData
-            Query result as a PyTorch Geometric graph.
+            Query result as a PyTorch Geometric graph. Containing numeric or boolean node properties
+            and edge_index tensor.
+        dict
+            A dictionary that maps the positional offset of each node in Data/HeteroData to its primary
+            key in the database.
+        dict
+            A dictionary contains node properties that cannot be converted into tensor automatically. The
+            order of values for each property is aligned with nodes in Data/HeteroData.
+        dict
+            A dictionary contains edge properties. The order of values for each property is aligned with
+            edge_index in Data/HeteroData.
         """
 
         self.check_for_query_result_close()