Multi-hop Question Answering via Reasoning Chains
Table 2: The blind test set performance achieved by our model on WikiHop and HotpotQA. On HotpotQA, all published works except DecompRC use the annotated supporting facts as extra supervision, which makes them not directly comparable to our model. However, our model still achieves strong performance on this dataset despite not using this annotation.
['[EMPTY]', 'EM', 'F1', 'Supp?']
We evaluate our best system from the prior section (BERT-Para with top-5 chains) on the blind test sets of our two datasets. On WikiHop, our model significantly outperforms past models, although these models do not use BERT. For HotpotQA, we use RoBERTa (Liu et al., This indicates that our heuristically-extracted chains can stand in effectively for this supervision, which suggests that our approach can generalize to settings where this annotation is not available.