---
license: mit
task_categories:
- text-classification
- text-generation
tags:
- nlp
- text
- text classification
- text generation
- error
- error correction
- synthetic
- generated
- ocr
- text-correction
- code-correction
---
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_\:\ \:\ \ /:/ /:/ _/_ /:/ /::\__\ __|:|__| /:/ \:\ \ /:/ /::\ \
/\ \:\ \:\__\ /:/_/:/ /\__\ /:/_/:/\:|__| /::::\__\_____ /:/__/ \:\__\ /:/_/:/\:\__\
\:\ \:\/:/ / \:\/:/ /:/ / \:\/:/ /:/ / ~~~~\::::/___/ \:\ \ /:/ / \:\/:/ /:/ /
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# Synthetic Error Correction
*UNDER DEVELOPMENT*
Small synthetic dataset (28 examples: 22 train, 6 test) of error-correction pairs for training text correction models (e.g., OCR post-processing, typos).
## Dataset Summary
This dataset was generated locally using the TYPE/RIGHTER offline-first PWA. It contains synthetic error-correction pairs for training text correction models.
*Generated by TYPE/RIGHTER • Offline-First PWA, downloadable in the /typerighter/ folder of the repo*
## Supported Tasks and Leaderboards
- Text error correction
- OCR post-processing
- Typographical error correction
## Languages
English
## Dataset Structure
### Data Instances
Each instance contains:
- `original`: The text as it appeared in the uploaded file
- `corrupted`: The procedurally "damaged" version for error detection training
- `target`: The cleaned, normalized version for error correction training
- `tags`: Content-based classification tags
- `source`: Original file name
### Data Fields
- `original`: string - Original text
- `corrupted`: string - Text with injected errors
- `target`: string - Cleaned target text
- `tags`: Sequence[string] - Content classification tags
- `source`: string - Source file name
### Data Splits
- Train: 22 examples
- Test: 6 examples
## Dataset Creation
### Curation Rationale
This dataset was created to provide synthetic data for training error correction models from user-provided documents.
### Source Data
The data was generated from user-uploaded documents in .txt, .csv, .md, or .jsonl formats.
### Annotations
Annotations were automatically generated through:
1. Text normalization (simulated cleaning)
2. Controlled error injection based on configurable parameters
3. Content-based classification
### Personal and Sensitive Information
All processing occurs locally in the browser. No data was uploaded to any server.
## Considerations for Using the Data
### Social Impact of Dataset
This dataset enables the creation of error correction models for various text domains.
### Discussion of Biases
The error patterns are synthetic and may not perfectly represent real-world error distributions.
### Other Known Limitations
- Synthetic errors may not capture all real-world error patterns
- Limited to text-based errors (no formatting or layout errors)
## Additional Information
### Dataset Curators
Generated by TYPE/RIGHTER PWA by webXOS
### Licensing Information
MIT
### Citation Information
```
@misc{typerighter2026,
title={TYPE/RIGHTER Synthetic Error Correction Dataset},
author={TYPE/RIGHTER PWA},
year={2026},
url={https://github.com/typerighter}
}
```
### Contributions
Thanks to the user who generated this dataset using TYPE/RIGHTER.
## Error Distribution
- Keyboard Adjacent Errors: 20%
- Case Corruption: 15%
- Symbol Insertion: 10%
- OCR Line Noise: 10%
## Generated on
2026-01-07T01:04:58.601Z
---
*Generated by TYPE/RIGHTER • Offline-First PWA • Privacy by Design • webXOS 2026*