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.

MTR-QA数据集（MTR-QA dataset）共收录24312条推理样本，涵盖8740条逻辑推理（logical reasoning）样本、9105条语义推理（semantic reasoning）样本、2647条数学推理（mathematical reasoning）样本以及3818条综合知识推理（comprehensive knowledge reasoning）样本，数据集总大小为34MB，以JSON格式（JSON format）存储。每个JSON对象包含六个属性：指令（Instruction）、问题（Question）、答案（Answer）、思维链（chain of thought）、标签（Label，原文存在拼写失误，原拼写为Lable）以及难度等级（Difficulty），各属性分别对应用户提供的指令、题目备选项、正确答案、解题思维链、题目推理类型与题目难度等级。其中，标签用于标识不同推理类型，可划分为逻辑推理、语义推理、数学推理与综合知识推理四类；难度等级则依据语言复杂度、解题步骤数与知识点复杂度，划分为初级、中级与高级三个层级，该分级方法可清晰量化评估题目难度。

搜集汇总

背景与挑战

背景概述

MTR-QA是一个多类型推理问答数据集，包含24,312条数据，涵盖逻辑、语义、数学和综合知识推理四种类型，数据以JSON格式存储，每个条目包含指令、问题、答案、思维链、推理类型和难度等级等六个属性。该数据集按语言难度、解题步骤和知识点复杂度将难度分为初级、中级和高级三个级别，用于评估推理任务的难易程度。