Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering

Understand

Commonsense question answering aims to answer questions which require background knowledge that is not explicitly expressed in the question.

• The key challenge is how to obtain evidence from external knowledge and make predictions based on the evidence.
• Recent works either learn to generate evidence from human-annotated evidence which is expensive to collect, or extract evidence from either structured or unstructured knowledge bases which fails to take advantages of both sources.
• In this work, we propose to automatically extract evidence from heterogeneous knowledge sources, and answer questions based on the extracted evidence.