diff --git a/dataManager/gFunDataset.py b/dataManager/gFunDataset.py
index adf38fa..9374fa1 100644
--- a/dataManager/gFunDataset.py
+++ b/dataManager/gFunDataset.py
@@ -106,7 +106,6 @@ class SimpleGfunDataset:
     
         return self.tr_langs, self.te_langs, self.all_langs
     
-
     def _set_datalang(self, data: pd.DataFrame):
         return {lang: data[data.lang == lang] for lang in self.all_langs}
 
@@ -162,6 +161,9 @@ class SimpleGfunDataset:
         one_hot_matrix = np.zeros((len(indices), n_labels))
         one_hot_matrix[np.arange(len(indices)), indices] = 1
         return one_hot_matrix
+    
+    def get_name(self):
+        return self.name
 
 
 def _mask_numbers(data):
diff --git a/infer.py b/infer.py
index 39bffce..0a57378 100644
--- a/infer.py
+++ b/infer.py
@@ -2,9 +2,11 @@ from dataManager.gFunDataset import SimpleGfunDataset
 from gfun.generalizedFunnelling import GeneralizedFunnelling
 from main import save_preds
 
+DATASET_NAME = "inference-dataset" # can be anything
+
 def main(args):
     dataset = SimpleGfunDataset(
-        dataset_name="inference-dataset",
+        dataset_name=DATASET_NAME,
         datadir=args.datadir,
         multilabel=False,
         only_inference=True,
@@ -15,7 +17,7 @@ def main(args):
     print("Ok")
 
     gfun = GeneralizedFunnelling(
-        dataset_name="inference",
+        dataset_name=dataset.get_name(),
         langs=dataset.langs(),
         num_labels=dataset.num_labels(),
         classification_type="singlelabel",
@@ -31,7 +33,7 @@ def main(args):
     save_preds(
         preds=predictions,
         targets=None,
-        config="inference"
+        config=f"Inference dataset: {dataset.get_name()}"
     )
 
 if __name__ == "__main__":
diff --git a/main.py b/main.py
index 8fa47a4..b4d452f 100644
--- a/main.py
+++ b/main.py
@@ -1,3 +1,4 @@
+import os
 from argparse import ArgumentParser
 from time import time
 
@@ -138,6 +139,7 @@ def main(args):
 
 
 def save_preds(preds, targets, config="unk", dataset="unk"):
+    os.makedirs("results/preds")
     df = pd.DataFrame()
     langs = sorted(preds.keys())
     _preds = []