diff --git a/scripts/GNN_topk_analysis.py b/scripts/GNN_topk_analysis.py
index 9ae9078d7..9d2d3a787 100644
--- a/scripts/GNN_topk_analysis.py
+++ b/scripts/GNN_topk_analysis.py
@@ -54,7 +54,7 @@ def main() -> None:
 
     in_domain_objects = parse_in_domain_objects(input_dir)
     object_counts = {in_domain_object: 0 for in_domain_object in in_domain_objects}
-    GNN_rank_matrix = [[0 for _ in range(len(in_domain_objects))] for _ in range(len(in_domain_objects))]
+    gnn_rank_matrix = [[0 for _ in range(len(in_domain_objects))] for _ in range(len(in_domain_objects))]
     for feature_file_path in sorted(input_dir.glob("situation*")):
         with open(feature_file_path / 'description.yaml', encoding="utf-8") as description_file:
             description_yaml = yaml.safe_load(description_file)
@@ -66,10 +66,10 @@ def main() -> None:
             for i in range(len(gnn_objects)):
                 gnn_object = gnn_objects[i]
                 if gnn_object == 'small_single_mug': gnn_object = 'mug'
-                GNN_rank_matrix[in_domain_objects.index(expected_object)][in_domain_objects.index(gnn_object)] += len(gnn_objects) - i
-    for object_id in range(len(GNN_rank_matrix)):
-        GNN_rank_matrix[object_id] = [label_count / object_counts[in_domain_objects[object_id]] for label_count in arr[object_id]]
-    df = pd.DataFrame(GNN_rank_matrix, in_domain_objects, in_domain_objects)
+                gnn_rank_matrix[in_domain_objects.index(expected_object)][in_domain_objects.index(gnn_object)] += len(gnn_objects) - i
+    for object_id in range(len(gnn_rank_matrix)):
+        gnn_rank_matrix[object_id] = [label_count / object_counts[in_domain_objects[object_id]] for label_count in arr[object_id]]
+    df = pd.DataFrame(gnn_rank_matrix, in_domain_objects, in_domain_objects)
     sn.set(font_scale=0.9)
     sn.color_palette('colorblind')
     sn.set_context('paper')