FOL-nli / README.md
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---
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}
}
```