WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-Hop Inference

Understand

Developing methods of automated inference that are able to provide users with compelling human-readable justifications for why the answer to a question is correct is critical for domains such as science and medicine, where user trust and detecting costly errors are limiting factors to adoption.

• One of the central barriers to training question answering models on explainable inference tasks is the lack of gold explanations to serve as training data.
• In this paper we present a corpus of explanations for standardized science exams, a recent challenge task for question answering.
• We manually construct a corpus of detailed explanations for nearly all publicly available standardized elementary science question (approximately 1,680 3rd through 5th grade questions) and represent these as "explanation graphs" -- sets of lexically overlapping sentences that describe how to arrive at the correct answer to a question through a combination of domain and world knowledge.