leobertolazzi/syllogistic-logic

Dataset Summary

Syllogistic-logic is a synthetic dataset designed to evaluate the logical reasoning abilities of LLMs. It focuses on the task of logical premise selection — identifying the minimal set of premises in a knowledge base that entails a given hypothesis. The dataset is built on the syllogistic fragment of first-order logic and supports systematic generalization experiments, including generalization to unseen knowledge bases and reasoning with longer or shorter inference chains than seen during training.

The dataset is used to train and evaluate models using the MIND (Meta-learning for IN-context Deduction) fine-tuning approach, which adapts few-shot meta-learning to logical reasoning. Each row in the dataset includes a knowledge base, study examples (support), a query hypothesis, and the set of premises from which the query hypothesis can be derived.

Further details can be found in the paper where the dataset was proposed: A MIND for Reasoning: Meta-learning for In-context Deduction

Features

Each example in the dataset includes the following fields:

Column	Type	Description
knowledge_base	string	Concatenated premises representing the KB.
study_examples_all	string	Concatenated study (support) examples for core generalization (see paper).
study_examples_comp	string	Concatenated study (support) examples for long->short generalization (see paper).
study_examples_rec	string	Concatenated study (support) examples for short->long generalization (see paper).
query_hyp	string	Query hypothesis to be proven.
query_inf	string	Minimal set of premises within KB that entail the query hypothesis.
kb_id	string	Identifier of the knowledge base.
pword_a	int64	Pseudowords assignment.
kb_permut	int64	Permutation index of the orderd of premises within KB.
#prem_kb	int64	Total premises in the KB.
inf_length	int64	Number of minimal premises necessary to derive the query hypotheisis.
inf_type	int64	Type of syllogistic inference (from 1 to 7).

To load the dataset, run:

from datasets import load_dataset

data_files = {
  "train": "train.csv",
  "validation": "validation.csv",
  "test": "test.csv",
  "test_ood_constants": "test_ood_constants.csv",
  "test_ood_support": "test_ood_support.csv",
  "test_ood_words": "test_ood_words.csv",
}
full_data = load_dataset("leobertolazzi/syllogistic-logic", data_files=data_files)

Licensing

This dataset is licensed under a CC BY-SA 4.0 License.

Cite

@misc{bertolazzi-et-al-2025-mind,
      title={A MIND for Reasoning: Meta-learning for In-context Deduction}, 
      author={Leonardo Bertolazzi and Manuel Vargas Guzmán and Raffaella Bernardi and Maciej Malicki and Jakub Szymanik},
      year={2025},
      eprint={2505.14313},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.14313}, 
}