Answering questions by learning to rank -- Learning to rank by answering questions

Understand

Answering multiple-choice questions in a setting in which no supporting documents are explicitly provided continues to stand as a core problem in natural language processing.

• The contribution of this article is two-fold.
• First, it describes a method which can be used to semantically rank documents extracted from Wikipedia or similar natural language corpora.
• Second, we propose a model employing the semantic ranking that holds the first place in two of the most popular leaderboards for answering multiple-choice questions: ARC Easy and Challenge.