---
language:
- en
license: apache-2.0
task_categories:
- text-classification
tags:
- data-cleaning
- corpus-filtering
- text-quality
- ultrax
size_categories:
- 1M<n<10M
---

# UltraX Line Classification Dataset

This dataset provides line-level annotations extracted from large English corpora to determine whether individual lines should be **kept**, **deleted**, or **revised** for data cleaning and curation.

> [!NOTE]
> This dataset is inspired by the UltraX project but is not officially affiliated with it. No proprietary artifacts from the original project are republished here.

## Methodology

1. **Data Collection:** 50,000 rows were sampled from each configuration of [openbmb/UltraX-Preview](https://huggingface.co/datasets/openbmb/UltraX-Preview).
2. **Line Comparison:** Raw and cleaned text versions from each row were compared to classify individual lines into mutually exclusive categories:
   - **Keep:** Lines retained in the final clean text.
   - **Delete:** Lines removed during the cleaning process.
   - **Edit:** Lines that underwent revision between the raw and clean versions.
3. **Splitting:** The dataset uses a stratified split into **train (80%)**, **validation (10%)**, and **test (10%)**.

### Class Distribution

| Label | Train | Validation | Test | Total |
| :--- | ---: | ---: | ---: | ---: |
| **Delete** | 644,545 | 80,568 | 80,568 | 805,681 |
| **Edit** | 46,964 | 5,871 | 5,871 | 58,706 |
| **Keep** | 3,518,387 | 439,798 | 439,799 | 4,397,984 |
| **Total** | **4,209,896** | **526,237** | **526,238** | **5,262,371** |

## Limitations

- **Class Imbalance:** The dataset is heavily imbalanced, reflecting real-world data cleaning distributions (the vast majority of lines are kept, fewer are deleted, and only a small fraction are edited).
- **Context Dependency:** Annotations are performed at the line level, which may occasionally lack broader document context (e.g., a specific line might serve as a valid title in one document but an irrelevant footnote in another).
- **Formatting Artifacts:** Potential structural quirks or formatting artifacts may persist from the raw text inputs.

## License

Distributed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).