---
dataset_info:
- config_name: default
  features:
  - name: version
    dtype: string
  - name: hypothesis
    dtype: string
  - name: hypothesis_formula
    dtype: string
  - name: context
    dtype: string
  - name: context_formula
    dtype: string
  - name: proofs
    sequence: string
  - name: proofs_formula
    sequence: string
  - name: negative_hypothesis
    dtype: string
  - name: negative_hypothesis_formula
    dtype: string
  - name: negative_proofs
    sequence: string
  - name: negative_original_tree_depth
    dtype: int64
  - name: original_tree_depth
    dtype: int64
  - name: depth
    dtype: int64
  - name: num_formula_distractors
    dtype: int64
  - name: num_translation_distractors
    dtype: int64
  - name: num_all_distractors
    dtype: int64
  - name: proof_label
    dtype: string
  - name: negative_proof_label
    dtype: string
  - name: world_assump_label
    dtype: string
  - name: negative_world_assump_label
    dtype: string
  - name: prompt_serial
    dtype: string
  - name: proof_serial
    dtype: string
  splits:
  - name: train
    num_bytes: 101861795
    num_examples: 30000
  - name: validation
    num_bytes: 16956757
    num_examples: 5000
  - name: test
    num_bytes: 16952009
    num_examples: 5000
  download_size: 50451962
  dataset_size: 135770561
- config_name: star
  features:
  - name: version
    dtype: string
  - name: hypothesis
    dtype: string
  - name: hypothesis_formula
    dtype: string
  - name: negative_hypothesis
    dtype: string
  - name: negative_hypothesis_formula
    dtype: string
  - name: negative_original_tree_depth
    dtype: int64
  - name: original_tree_depth
    dtype: int64
  - name: depth
    dtype: int64
  - name: num_formula_distractors
    dtype: int64
  - name: num_translation_distractors
    dtype: int64
  - name: num_all_distractors
    dtype: int64
  - name: proof_label
    dtype: string
  - name: negative_proof_label
    dtype: string
  - name: world_assump_label
    dtype: string
  - name: negative_world_assump_label
    dtype: string
  - name: facts
    dtype: string
  - name: facts_formula
    dtype: string
  - name: proofs
    sequence: string
  - name: proofs_formula
    sequence: string
  - name: negative_proofs
    sequence: string
  - name: prompt_serial
    dtype: string
  - name: proof_serial
    dtype: string
  splits:
  - name: train
    num_bytes: 126945152
    num_examples: 30000
  - name: validation
    num_bytes: 21067447
    num_examples: 5000
  - name: test
    num_bytes: 21287828
    num_examples: 5000
  download_size: 61766317
  dataset_size: 169300427
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
- config_name: star
  data_files:
  - split: train
    path: star/train-*
  - split: validation
    path: star/validation-*
  - split: test
    path: star/test-*
---
# Dataset Card for "FLD.v2"
To train a casual language model, simply use "prompt_serial" column for the model input and "proof_serial" for the output.
For more info, see [our project page](https://github.com/hitachi-nlp/FLD/).

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)