MTR-QA：Multi-Type Reasoning Question Answering Dataset

The MTR-QA dataset contains 24,312 reasoning data, including 8,740 logical reasoning data, 9,105 semantic reasoning data, 2,647 mathematical reasoning data, and 3,818 comprehensive knowledge reasoning data, with the size of 34MB.1 MB, which are stored in JSON format, and each JSON object has six attributes: Instruction, Question, Each JSON object has six attributes: Instruction, Question, Answer, Target, Lable, and Difficulty, which correspond to the instruction suggested by the user, the option provided by the user, the correct answer, the chain of thought, the reasoning type of the question, and the difficulty level of the question, respectively.

Among them, lable corresponds to different types of reasoning, which are categorized into logical reasoning, semantic reasoning, mathematical reasoning, and comprehensive knowledge reasoning; difficulty is categorized into primary, intermediate, and advanced difficulty levels according to the degree of difficulty of the language, the steps of solving the problem, and the complexity of the knowledge points, and the grading method can clearly evaluate the degree of difficulty.