---
language:
- en
- cy
license: other
task_categories:
- translation
- text-generation
size_categories:
- 10K<n<100K
tags:
- welsh
- cymraeg
- parallel-corpus
- instruction-tuning
- sft
---

# UK Legislation — Welsh–English SFT Dataset

Processed instruction-tuning dataset derived from `techiaith/legislation-gov-uk_en-cy`, a Welsh–English parallel translation memory published by the Bangor University Language Technologies Unit (Techiaith). Formatted for supervised fine-tuning (SFT) of language models.

## Source

| Field | Value |
|-------|-------|
| Source dataset | [`techiaith/legislation-gov-uk_en-cy`](https://huggingface.co/datasets/techiaith/legislation-gov-uk_en-cy) |
| Domain | UK statute law (legislation.gov.uk) |
| Raw pairs | 64,726 |
| Processed examples | 17,886 |
| Licence | Open Government Licence v3.0 (OGL) |

All translations were produced by professional translators working within Welsh public sector institutions.

## Format

The dataset uses the messages chat format. Two example types are included.

**Single-turn** (~70% of examples):
```json
{
  "messages": [
    {
      "role": "user",
      "content": "Translate the following English text into Welsh:\n\nThe application must be submitted before the deadline."
    },
    {
      "role": "assistant",
      "content": "Rhaid cyflwyno'r cais cyn y dyddiad cau."
    }
  ],
  "source_dataset": "techiaith/legislation-gov-uk_en-cy"
}
```

**Multi-turn** (~30% of examples):
```json
{
  "messages": [
    {
      "role": "user",
      "content": "I'd like you to translate a series of English sentences into Welsh. I'll give you one sentence at a time.\n\nThe committee has considered this matter in detail."
    },
    {
      "role": "assistant",
      "content": "Mae'r pwyllgor wedi ystyried y mater hwn yn fanwl."
    },
    {
      "role": "user",
      "content": "An amendment was proposed by the Member for Ynys Môn."
    },
    {
      "role": "assistant",
      "content": "Cynigiwyd gwelliant gan yr Aelod dros Fôn."
    }
  ],
  "source_dataset": "techiaith/legislation-gov-uk_en-cy"
}
```

**Fields:**
- `messages`: Translation task in chat format
- `source_dataset`: HuggingFace ID of the originating source corpus

The dataset is balanced: ~50% English→Welsh and ~50% Welsh→English translations. Instruction prompts are drawn from a diverse pool of 21 template phrasings in both English and Welsh to reduce overfitting to a single prompt pattern.

## Curation Pipeline

Raw pairs from the source dataset were processed through the following stages:

1. **Length filter** — pairs where either side is fewer than 20 characters are removed
2. **Artefact filter** — pairs containing URLs, emoji, bullet/list markers, or excessive repetition are removed
3. **Exact deduplication** — normalised string deduplication (NFC, lowercased, whitespace-collapsed)
4. **MinHash deduplication** — 1-gram MinHash LSH (128 permutations, Jaccard threshold 0.9) to remove near-identical surface-form variants
5. **Semantic deduplication** — embedding-based deduplication via SemHash (`minishlab/potion-multilingual-8M`, cosine threshold 0.85) to remove semantically equivalent pairs with different surface forms
6. **Instruction formatting** — conversion to chat format with template diversity and multi-turn conversation grouping

## Limitations

All source data is drawn from formal institutional domains. The dataset covers formal Welsh well but underrepresents colloquial, spoken, and informal registers. Source translation memories may contain a small number of misaligned pairs that are not detectable without a dedicated quality scorer.

## Citation

If you use this dataset, please cite the original Techiaith source:

```bibtex
@misc{techiaith_legislation_gov_uk,
  author       = {{Bangor University Language Technologies Unit (Techiaith)}},
  title        = {legislation.gov.uk Welsh–English Translation Memory},
  year         = {2023},
  publisher    = {HuggingFace},
  howpublished = {\url{https://huggingface.co/datasets/techiaith/legislation-gov-uk_en-cy}},
}
```

## Acknowledgements

- [Techiaith (Bangor University)](https://techiaith.cymru/) for producing and releasing the source translation memories
- [Locai Labs](https://huggingface.co/locailabs) for the curation pipeline