---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: premise
    dtype: string
  - name: hypothesis
    dtype: string
  - name: label
    dtype: string
  - name: premise_tptp
    dtype: string
  - name: hypothesis_tptp
    dtype: string
  - name: proof_inputs
    sequence: string
  - name: proof
    dtype: string
  - name: rule_concentration
    dtype: float64
  splits:
  - name: train
    num_bytes: 545983394.2802362
    num_examples: 82219
  - name: validation
    num_bytes: 68252074.65929127
    num_examples: 10278
  - name: test
    num_bytes: 68245434.06047249
    num_examples: 10277
  download_size: 182483284
  dataset_size: 682480903
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- logic
- reasoning
- fol
- first-order-logic
---
# Dataset Card for "FOL-nli"

https://github.com/sileod/unigram/

```
@article{sileo2024scaling,
  title={Scaling Synthetic Logical Reasoning Datasets with Context-Sensitive Declarative Grammars},
  author={Sileo, Damien},
  journal={arXiv preprint arXiv:2406.11035},
  year={2024}
}
```