README.md

metadata

license: mit
task_categories:
  - question-answering
  - text-classification
language:
  - en
arxiv: 2501.14851

JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models

[Paper] [Github]

JustLogic is a deductive reasoning datataset that is

1. highly complex, capable of generating a diverse range of linguistic patterns, vocabulary, and argument structures;
2. prior knowledge independent, eliminating the advantage of models possessing prior knowledge and ensuring that only deductive reasoning is used to answer questions; and
3. capable of in-depth error analysis on the heterogeneous effects of reasoning depth and argument form on model accuracy.

Dataset Format

• premises: List of premises in the question, in the form of a Python list.
• paragraph: A paragraph consisting of the above premises. This is given as input to models.
• conclusion: The expected conclusion of the given premises.
• question: The statement in which models must determine its truth-value.
• label: True | False | Uncertain
• arg: The argument structure
• statements: Matching symbols in arg to their corresponding natural language statements.
• depth: The argument depth of the given question

Dataset Construction

JustLogic is a synthetically generated dataset. The script to construct your own dataset can be found in the Github repo.

Citation

@article{chen2025justlogic,
  title={JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models},
  author={Chen, Michael K and Zhang, Xikun and Tao, Dacheng},
  journal={arXiv preprint arXiv:2501.14851},
  year={2025}
}

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license: mit