diff --git a/eval_scripts/citation_eval.py b/eval_scripts/citation_eval.py
index 3707a53..feb69cc 100644
--- a/eval_scripts/citation_eval.py
+++ b/eval_scripts/citation_eval.py
@@ -31,11 +31,11 @@ def run_regression(train_embeds, train_labels, test_embeds, test_labels):
 if __name__ == '__main__':
     parser = ArgumentParser("Run evaluation on citation data.")
     parser.add_argument("dataset_dir", help="Path to directory containing the dataset.")
-    parser.add_argument("data_dir", help="Path to directory containing the learned node embeddings.")
+    parser.add_argument("embed_dir", help="Path to directory containing the learned node embeddings.")
     parser.add_argument("setting", help="Either val or test.")
     args = parser.parse_args()
     dataset_dir = args.dataset_dir
-    data_dir = args.data_dir
+    data_dir = args.embed_dir
     setting = args.setting
 
     print("Loading data...")
diff --git a/eval_scripts/ppi_eval.py b/eval_scripts/ppi_eval.py
index 88b7a9e..9348926 100644
--- a/eval_scripts/ppi_eval.py
+++ b/eval_scripts/ppi_eval.py
@@ -21,11 +21,11 @@ def run_regression(train_embeds, train_labels, test_embeds, test_labels):
 if __name__ == '__main__':
     parser = ArgumentParser("Run evaluation on PPI data.")
     parser.add_argument("dataset_dir", help="Path to directory containing the dataset.")
-    parser.add_argument("data_dir", help="Path to directory containing the learned node embeddings. Set to 'feat' for raw features.")
+    parser.add_argument("embed_dir", help="Path to directory containing the learned node embeddings. Set to 'feat' for raw features.")
     parser.add_argument("setting", help="Either val or test.")
     args = parser.parse_args()
     dataset_dir = args.dataset_dir
-    data_dir = args.data_dir
+    data_dir = args.embed_dir
     setting = args.setting
 
     print("Loading data...")
diff --git a/eval_scripts/reddit_eval.py b/eval_scripts/reddit_eval.py
index a0f68c6..7161084 100644
--- a/eval_scripts/reddit_eval.py
+++ b/eval_scripts/reddit_eval.py
@@ -24,11 +24,11 @@ def run_regression(train_embeds, train_labels, test_embeds, test_labels):
 if __name__ == '__main__':
     parser = ArgumentParser("Run evaluation on Reddit data.")
     parser.add_argument("dataset_dir", help="Path to directory containing the dataset.")
-    parser.add_argument("data_dir", help="Path to directory containing the learned node embeddings. Set to 'feat' for raw features.")
+    parser.add_argument("embed_dir", help="Path to directory containing the learned node embeddings. Set to 'feat' for raw features.")
     parser.add_argument("setting", help="Either val or test.")
     args = parser.parse_args()
     dataset_dir = args.dataset_dir
-    data_dir = args.data_dir
+    data_dir = args.embed_dir
     setting = args.setting
 
     print("Loading data...")
diff --git a/graphsage/minibatch.py b/graphsage/minibatch.py
index 60c7b97..1cfd6d9 100644
--- a/graphsage/minibatch.py
+++ b/graphsage/minibatch.py
@@ -59,13 +59,18 @@ class EdgeMinibatchIterator(object):
 
     def _remove_isolated(self, edge_list):
         new_edge_list = []
+        missing = 0
         for n1, n2 in edge_list:
+            if not n1 in self.G.node or not n2 in self.G.node:
+                missing += 1
+                continue
             if (self.deg[self.id2idx[n1]] == 0 or self.deg[self.id2idx[n2]] == 0) \
                     and (not self.G.node[n1]['test'] or self.G.node[n1]['val']) \
                     and (not self.G.node[n2]['test'] or self.G.node[n2]['val']):
                 continue
             else:
                 new_edge_list.append((n1,n2))
+        print("Unexpected missing:", missing)
         return new_edge_list
 
     def construct_adj(self):