Dynamic Knowledge Graph Construction for Zero-shot Commonsense Question Answering
Table 3: Effect of the decoding algorithm for generating commonsense inferences from ℂ𝕆𝕄𝔼𝕋. All results on SocialIQa development set.
['[BOLD] Decoding Algorithm', '[BOLD] CGA [ITALIC] max', '[BOLD] CGA']
This result is promising as it shows that the reasoning procedure is robust to variability in the candidate generations. However, it also depicts the weakness of using exact inference or maximum likelihood estimation for reasoning over the graph, as these approaches are not capable of leveraging larger candidate sets of commonsense knowledge to answer questions correctly. These results point to the need for future work in developing algorithms that can leverage diverse commonsense inference paths for reasoning over dynamically constructed knowledge graphs.