Before revision:  Our contributions are as follows . i) We outperform BERT on cloze-style QA by large margins without any further training. ii) We show that BERT often identifies the correct response category (e.g., central European city), but only kNN recovers the factually correct answer (e.g., " Vienna ")  .
After revision:  Our contributions are as follows . i) We outperform BERT on cloze-style QA by large margins without any further training. ii) We show that BERT often identifies the correct response category (e.g., central European city), but only kNN recovers the factually correct answer (e.g., " Vienna ") . iii) Compared to BERT, BERT-kNN excels for rare facts. iv) BERT-kNN can easily handle facts not covered by BERT's training set, e.g., recent events .