added confidence

generic_nel.py

@@ -116,7 +116,11 @@ class NelPipeline(Pipeline):
         )
         # print(outputs)
         token_ids, scores = outputs.sequences, outputs.scores
-
+        # Decode the predictions into readable text
+        wikipedia_predictions = self.tokenizer.batch_decode(
+            outputs, skip_special_tokens=True
+        )
+        print(wikipedia_predictions)
         print(len(scores))
         for score in scores:
             print(score.shape)
@@ -125,11 +129,6 @@ class NelPipeline(Pipeline):
         probabilities = torch.exp(scores_tensor)
         percentages = (probabilities * 100.0).cpu().numpy().tolist()
 
-        # Decode the predictions into readable text
-        wikipedia_predictions = self.tokenizer.batch_decode(
-            outputs, skip_special_tokens=True
-        )
-
         # Return the predictions along with the extracted entity, lOffset, and rOffset
         return wikipedia_predictions, enclosed_entity, lOffset, rOffset, percentages