Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction
Table 11: Performance of evidence extraction. The top five rows are evaluated on the test set. The comparison of our models is on the development set. The models submitted after the Shared Task have no information about precision or recall.
['[EMPTY]', 'Precision', 'Recall', 'F1']
What are the characteristics of our evidence extraction? On the test set, it ranked in 2nd place in precision, 3rd place in recall, and 1st place in F1. As for the results on the development set, QFE extracted with higher precision than recall. This tendency was the same as in the RC evaluation. The single model has a larger difference between precision and recall. The ensemble model improves recall and F1.