Update app.py

app.py

@@ -111,8 +111,10 @@ class NounExtractor:
         """
         Determine the most appropriate dependency label for a phrase based on internal dependencies.
         """
-        if 'nsubj' in deps_in_phrase or 'nsubjpass' in deps_in_phrase:
-            return 'ROOT'
+        if 'nsubj' in deps_in_phrase:
+            return 'ROOTnsubj'
+        elif 'nsubjpass' in deps_in_phrase:
+            return 'ROOTnsubjpass'
         else:
             # Choose a representative dependency if no clear subject is present
             return deps_in_phrase.pop() if deps_in_phrase else 'unknown'
@@ -130,7 +132,7 @@ class NounExtractor:
         if found_verbs:
             # Adjust dependency labels for noun phrases based on the presence of an causative verb.
             for phrase, dep in list(result_dict.items()):  # Work on a copy of items to safely modify the dict
-                if dep == 'ROOT':
+                if dep == 'ROOTnsubj':
                     result_dict[phrase] = 'dobj'
                 elif dep == 'dobj':
                     result_dict[phrase] = 'ROOT'
@@ -140,13 +142,13 @@ class NounExtractor:
 def format_results(results):
     formatted = []
     # Find all roots or central subjects to structure the phrases around them
-    root_keys = [key for key, value in results.items() if value == 'ROOT' or value == 'nsubjpass']
+    root_keys = [key for key, value in results.items() if value == 'ROOTnsubj' or value == 'ROOTnsubjpass']
 
     for key, value in results.items():
         if key in root_keys:
             continue  # Skip the roots themselves when adding to the formatted list
         for root_key in root_keys:
-            if value == 'nsubjpass':  # If the dependency indicates a passive subject
+            if value == 'ROOTnsubjpass':  # If the dependency indicates a passive subject
                 formatted.append(f"{key} -> {root_key}")
             else:
                 formatted.append(f"{root_key} <- {key}")