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Scenario-based question answering (SQA) has attracted increasing researchattention. It typically requires retrieving and integrating knowledge frommultiple sources, and applying general knowledge to a specific case describedby a scenario. SQA widely exists in the medical, geography, and legaldomains---both in practice and in the exams. In this paper, we introduce theGeoSQA dataset. It consists of 1,981 scenarios and 4,110 multiple-choicequestions in the geography domain at high school level, where diagrams (e.g.,maps, charts) have been manually annotated with natural language descriptionsto benefit NLP research. Benchmark results on a variety of state-of-the-artmethods for question answering, textual entailment, and reading comprehensiondemonstrate the unique challenges presented by SQA for future research.

GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level