We provide here a dataset for tasks related to natural language understanding and natural language inference. The dataset contains logical puzzles in natural language from three domains: comparing puzzles, knighs and knaves, and zebra puzzles. Each puzzle is associated with the entire set of atomic questions that can be generated based on the relations and individuals occurring in the text. For each question we provide the correct answer: entailment, contradiction or ambiguity. The answer's correctness is verified against theorem provers. Good puzzles have two properties: (i) each piece of information is necessary and (ii) no unnecessary information is provided. These properties make puzzles interesting candidates for machine comprehension tasks.
翻译：我们在此提供与自然语言理解和自然语言推断有关的任务的数据集。 数据集包含来自三个领域的自然语言的逻辑拼图: 比较拼图、 knighs 和 knaves 和 zebra 拼图。 每个拼图都与根据文本中出现的关系和个人产生的整个一组原子问题相关联。 对于每一个问题, 我们提供正确的答案: 包含、 矛盾或模糊。 答案的正确性会根据理论验证来验证。 良好的拼图有两个属性:(一) 每部分信息都是必要的, 并且 (二) 没有提供不必要的信息。 这些属性为机器理解任务提供了有趣的选择 。
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