README.md

---
license: cc-by-4.0
configs:
- config_name: madlibs
  data_files:
  - path:
    - madlibs.jsonl.zst
    split: train
- config_name: replacement
  data_files:
  - path:
    - replacement.jsonl.zst
    split: train
- config_name: scrambled
  data_files:
  - path:
    - scrambled.jsonl.zst
    split: train
task_categories:
- text-classification
language:
- en
---
# Garbled Text Dataset

This dataset contains superficially meaningful English text that entirely lacks global coherence and meaning.
While individual sentences in the `scrambled` and `replacement` subsets are grammatically valid, when combined, they do not form a cohesive narrative or logical text.
This dataset is designed to train models on **adversarial text classification**, natural language inference (NLI), and coherence detection.

## Dataset Summary

The dataset is derived from the `sample_k10000` split of the [agentlans/high-quality-text-long](https://huggingface.co/datasets/agentlans/high-quality-text-long) dataset.
Each row in this dataset directly maps to the corresponding row of the original source dataset, processed through three randomization algorithms.

### Supported Tasks and Leaderboards

* **Adversarial Text Classification / Coherence Detection:** The dataset can be used to train classifiers to distinguish between naturally cohesive text and algorithmic/artificial gibberish.

## Dataset Structure

### Data Subsets

The dataset is divided into three subsets based on the transformation algorithm applied:

| Split Name | Description | Linguistic Characteristics |
| --- | --- | --- |
| `scrambled` | Sentences from the original text are shuffled into a random order. | Locally grammatical; lacks global chronological or logical coherence. |
| `madlibs` | Nouns and verbs within the text are randomly permuted across the document. | Destroys syntax and local semantics; grammatically chaotic. |
| `replacement` | One-third (1/3) of the sentences in the original text are randomly replaced with sentences from [agentlans/high-quality-english-sentences](https://huggingface.co/datasets/agentlans/high-quality-english-sentences). | Disrupted narrative flow; contains sudden, completely unrelated topics. |

Sentence tokenization and Part-of-Speech (PoS) tagging for the transformations were performed using spaCy's `en_core_web_sm` pipeline.

## Limitations

* **Artificial Patterns:** The dataset relies on well-defined, randomized rule-based algorithms. Models trained heavily on this data may overfit to these specific algorithmic artifacts.
* **Scope of LLM Failures:** This dataset does not capture all common Large Language Model (LLM) degradation modes, such as repetitive loops, hallucinations, or subtle factual contradictions.
* **Not for Pre-training:**
> [!WARNING]
> **Do not** use this dataset for standard language modelling or pre-training production LLMs, as it will degrade their ability to generate coherent text.

## Additional Information

### Licensing

This dataset is licensed under the **Creative Commons Attribution 4.0 International** ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) license.

### Citation

*If you publish work or release a model based on this dataset, please cite it using the following format:*

```bibtex
@misc{garbled_text_dataset,
  author = {agentlans},
  title = {Garbled Text Dataset},
  year = {2026},
  publisher = {Hugging Face},
  journal = {Hugging Face Datasets},
  howpublished = {\url{https://huggingface.co/datasets/agentlans/garbled-text}}
}

```

## See Also

[agentlans/markov-slop](https://huggingface.co/datasets/agentlans/markov-slop) for text generation using another algorithm.