Before revision:  We propose an efficient differentiable model for multi-hop reasoning over knowledge facts, named DrFact. We evaluate our approach on a collection of re-formatted, open-ended versions of popular tests targeting commonsense reasoning , and show that our approach outperforms strong baseline methods by a large margin.
After revision:  We propose an efficient differentiable model for multi-hop Reasoning over knowledge Facts. To evaluate OpenCSR methods, we adapt several popular commonsense reasoning benchmarks, and collect multiple new answers for each test question via crowd-sourcing. Experiments show that DrFact outperforms strong baseline methods by a large margin.