fix premise

app.py

@@ -56,7 +56,7 @@ def gradio_formatter(js, output_type):
     elif output_type == 'z':
         data = {
             'Claim Phrase': js['claim_phrases'],
-            'Local Premise': [x[0] for x in js['local_premises']],
+            'Local Premise': js['local_premises'],
             'p_SUP': [round(x[2], 4) for x in js['phrase_veracity']],
             'p_REF': [round(x[0], 4) for x in js['phrase_veracity']],
             'p_NEI': [round(x[1], 4) for x in js['phrase_veracity']],
@@ -95,7 +95,7 @@ iface = gr.Interface(
               'The Cry of the Owl is based on a book by an American.',
               'Smriti Mandhana is an Indian woman.'],
     title="LOREN",
-    layout='vertical',
+    layout='horizontal',
     description="LOREN is an interpretable Fact Verification model against Wikipedia. "
                 "This is a demo system for \"LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification\". "
                 "See the paper for technical details. You can add FLAG on the bottom to record interesting or bad cases! \n"

src/loren.py

@@ -57,7 +57,7 @@ class Loren:
         label = id2label[y_predicted[0]]
 
         # Update js
-        js = assemble_answers_to_one(js, k=1)
+        js = assemble_answers_to_one(js, k=3)
         js['evidence'] = [self.fc_client.tokenizer.clean_up_tokenization(e[2]) for e in js['evidence']]
         js['questions'] = [self.fc_client.tokenizer.clean_up_tokenization(q) for q in js['questions']]
         js['claim_phrases'] = [self.fc_client.tokenizer.clean_up_tokenization(a[0]) for a in js['answers']]