---
license: apache-2.0
language:
- en
task_categories:
- text-generation
tags:
- bookcorpus
- gutenberg
- project-gutenberg
- philosophy
- classical-texts
- character-level
- curriculum-learning
- slm
size_categories:
- 10M<n<100M
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 2128762265
    num_examples: 13556975
  - name: validation
    num_bytes: 236146830
    num_examples: 1506331
  download_size: 1610933332
  dataset_size: 2364909095
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
---

# BookCorpus + Gutenberg Classics Training Corpus

Large-scale training corpus combining BookCorpus fiction, Project Gutenberg 19th-century literature (PG-19), and curated classical philosophy texts. Cleaned, deduplicated, and organized into curriculum phases for character-level language model training.

## Dataset Description

This corpus is the primary training dataset for the Julia SLM project, combining three major text sources into a unified, cleaned training set with curriculum-phase annotations for structured learning.

### Source Composition

| Source | Files | Chunks (pre-dedup) | Proportion |
|--------|------:|-------------------:|-----------:|
| [BookCorpus](https://huggingface.co/datasets/bookcorpus/bookcorpus) | 147 | 14,190,796 | 89.4% |
| [PG-19](https://huggingface.co/datasets/deepmind/pg19) (Project Gutenberg) | 552 | 1,344,777 | 8.5% |
| Classical Philosophy (MIT Classics, Internet Archive, Gutenberg) | 137 | 330,954 | 2.1% |
| **Total** | **836** | **15,866,527** | **100%** |

### Cleaning Applied

All text has been processed through a multi-stage cleaning pipeline:

- **Character filtering**: Lowercased to ASCII set `a-z .,;:?!'"()-`
- **Source-specific cleaning**:
  - BookCorpus: Moses-style detokenization (recombined subword artifacts)
  - PG-19: Gutenberg boilerplate header/footer removal
  - Philosophy: LaTeX artifact removal, footnote/reference stripping
- **Deduplication**: Exact dedup removed 803,221 duplicates (5.1%)
- **Whitespace normalization**: Multi-space collapse, empty line removal

### Curriculum Phases

The corpus is organized into three curriculum phases based on the classical trivium/quadrivium education model, suitable for DoReMi-style weighted phase sampling:

| Phase | Description | Train Chunks | Proportion |
|-------|-------------|-------------:|-----------:|
| **Trivium** | Grammar, rhetoric, logic (BookCorpus fiction, classical literature, rhetoric) | 13,475,278 | 99.4% |
| **Quadrivium** | Arithmetic, geometry, music, astronomy (Aristotle Physics, Plato Timaeus, Euclid) | 11,652 | 0.08% |
| **Philosophy** | Pure philosophy (Kant, Spinoza, Bacon, Seneca, Schopenhauer) | 70,042 | 0.52% |

Phase-specific training files are available in the `curriculum/` directory.

### Dataset Statistics

| Split | Examples | Size |
|-------|----------|------|
| Train | 13,556,974 | 2.0 GB |
| Validation | 1,506,330 | 221 MB |

- **90/10 train/validation split** (shuffled)
- **Weighted phase sampling** applied per config: trivium 40%, quadrivium 35%, philosophy 25%

### Philosophy Sources

The corpus includes texts from 50+ classical authors spanning Greek, Roman, Medieval, Enlightenment, and Modern philosophy:

**Greek**: Aristotle (Metaphysics, Nicomachean Ethics, Politics, Physics, Rhetoric, Poetics, Categories, Prior/Posterior Analytics, Topics, On the Soul, On the Heavens, On Interpretation, Generation and Corruption), Plato (Republic, Laws, Timaeus, Phaedo, Phaedrus, Symposium, Meno, Theaetetus, Protagoras), Herodotus, Thucydides, Xenophon, Aeschylus, Sophocles, Homer, Euripides

**Roman**: Marcus Aurelius, Seneca, Epictetus, Cicero, Lucretius, Plutarch, Tacitus, Virgil

**Medieval/Renaissance**: Boethius, Machiavelli, Thomas More

**Enlightenment**: Descartes, Spinoza, Leibniz, Locke, Berkeley, Hume, Kant, Rousseau, Montesquieu

**Modern**: Schopenhauer, Mill, Thoreau, William James

**Eastern**: Bhagavad Gita, Sun Tzu, Confucius, Lao Tzu

## Additional Files

The `curriculum/` directory contains phase-specific training files:
- `train_trivium.txt` - Grammar, rhetoric, and logic texts (2.0 GB)
- `train_quadrivium.txt` - Mathematical and natural philosophy texts (2.1 MB)
- `train_philosophy.txt` - Pure philosophy texts (13 MB)

## Usage

```python
from datasets import load_dataset

ds = load_dataset("LisaMegaWatts/bookcorpus-gutenberg-classics")

# Training data
for example in ds["train"]:
    text = example["text"]

# Download phase-specific files for curriculum training
from huggingface_hub import hf_hub_download

trivium = hf_hub_download(
    "LisaMegaWatts/bookcorpus-gutenberg-classics",
    "curriculum/train_trivium.txt",
    repo_type="dataset",
)
```

## Related Datasets

- [LisaMegaWatts/philosophy-corpus](https://huggingface.co/datasets/LisaMegaWatts/philosophy-corpus) - Isolated philosophy provenance dataset (for model training lineage)
- [LisaMegaWatts/wikitext-103-quality-scored](https://huggingface.co/datasets/LisaMegaWatts/wikitext-103-quality-scored) - Quality-scored WikiText-103 (Wikipedia Featured articles)
- [LisaMegaWatts/classical-humanities-corpus](https://huggingface.co/datasets/LisaMegaWatts/classical-humanities-corpus) - Extended classical humanities collection

## License

Apache 2.0