---
language:
- en
task_categories:
- text-classification
- token-classification
tags:
- json
- validation
- semantic-errors
- synthetic-data
size_categories:
- n<1K
---

# JSON SemVal Synthetic v1

Synthetic JSON+Schema corruptions for semantic validation training.

## Dataset Description

This dataset contains synthetically generated JSON payloads with controlled semantic errors for training ML models to detect and fix JSON validation issues.

### Dataset Structure

Each example in the dataset contains:

- `schema`: JSON Schema definition
- `clean_json`: Valid JSON payload conforming to the schema
- `corrupt_json`: Corrupted JSON with semantic errors
- `error_type`: Type of error introduced (e.g., type_mismatch, format_violation, enum_violation)
- `jsonpath`: JSONPath to the location of the error
- `fix_action`: Suggested fix action (e.g., cast_number, parse_date_iso, map_enum)

### Error Types

- `type_mismatch` - Wrong data type (e.g., string instead of integer)
- `format_violation` - Invalid format (e.g., bad date format)
- `enum_violation` - Invalid enum value
- `missing_required` - Missing required field
- `extra_property` - Unexpected additional property
- `range_violation` - Value outside allowed range
- `pattern_violation` - String doesn't match regex pattern

### Data Splits

- **Train**: 30 examples
- **Test**: 10 examples

### Usage

```python
from datasets import load_dataset

dataset = load_dataset("thearnabsarkar/json-semval-synth-v1")

# Access train split
train_data = dataset["train"]

# Example usage
for example in train_data:
    print(f"Error type: {example['error_type']}")
    print(f"JSONPath: {example['jsonpath']}")
    print(f"Fix action: {example['fix_action']}")
```

### Dataset Creation

This dataset was generated using the JSON Semantic Validator's synthetic data generation pipeline, which:

1. Generates diverse JSON schemas
2. Creates valid JSON payloads
3. Introduces controlled corruptions
4. Labels each corruption with error type and location

### License

MIT

### Citation

If you use this dataset, please cite:

```bibtex
@misc{json-semval-synth-v1,
  author = {Arnab Sarkar},
  title = {JSON SemVal Synthetic v1},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/thearnabsarkar/json-semval-synth-v1}
}
```

### Related Resources

- **Model**: [thearnabsarkar/json-semval-minilm-v1](https://huggingface.co/thearnabsarkar/json-semval-minilm-v1) (coming soon)
- **Space**: [thearnabsarkar/json-semantic-validator](https://huggingface.co/spaces/thearnabsarkar/json-semantic-validator) (coming soon)
- **Code**: [GitHub Repository](https://github.com/thearnabsarkar/json-semantic-validator) (if applicable)