CommonSenseQA
reasoning official site →
CommonSenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict correct answers. It contains 12,102 questions with one correct answer and four distractors, designed to test semantic reasoning and conceptual relationships. Questions are created based on ConceptNet concepts and require prior world knowledge for accurate reasoning.
Methodology
Imported from llm-stats public benchmark metadata. Modality: text. Max score: 1. Categories: language, reasoning. Language: en. Verified by llm-stats: no.