LogicalCOT

该数据集名为LogicalCOT，旨在通过多种任务，如将自然语言翻译成逻辑符号、推理链以及机器阅读理解等，来评估大型语言模型对逻辑理解能力的表现。该数据集包含了一系列需要上下文推理和理解逻辑陈述的任务，并以中文和英文为主要关注点。其任务范围涉及逻辑理解、推理以及推断。

The dataset, named LogicalCOT, is developed to evaluate the logical comprehension capabilities of large language models (LLMs) through a variety of tasks, including translating natural language into logical symbols, processing reasoning chains, and machine reading comprehension. It encompasses a series of tasks that require contextual reasoning and understanding of logical statements, with a primary focus on both Chinese and English languages. The scope of its tasks covers logical comprehension, reasoning, and inference.