Supervised fine-tuning (SFT) splits built from the swiss-ai/apertus-pretrain-rumansh corpus. It contains dictionary list translation, sentence-level translation, idiom identification, and a small set of human-translated Romansh instructions.

Source hub: https://huggingface.co/datasets/swiss-ai/apertus-pretrain-rumansh

Provenance

Dictionaries: All dictionary entries originate from Pledarigrond and are provided by the Lia Rumantscha. Includes idioms: Sursilvan, Sutsilvan, Surmiran, Rumantsch Grischun. Each entry forms a Prompt–Answer pair of the type:
- Prompt: "Übersetze die folgende Liste von <Idiom>-Begriffen ins Deutsche:\n{romansh_list}"
- Answer: "{german_list}"
- and the reverse: Prompt in German with Answer in Romansh.
Idiom identification: Labels derived from public text in La Quotidiana (see swiss-ai/apertus-pretrain-rumansh). Prompts follow the template:
- Prompt: "Sag mir in welchem Idiom der folgende Satz ist: {romansh_sentence}"
- Answer: "<Idiom>"
Human translations: Random sample from a filtered Tülü dataset prepared by the Swiss AI Initiative (link pending). Translated by volunteers via https://data-collection.swissai.cscs.ch/. Prize support: CHF 350.– from Prof. Antoine Bosselut. Released under CC BY 4.0.
Synthetic translations: Sentence-level alignment was performed bidirectionally (German ↔ Idiom, Multilingual ↔ Rumantsch Grischun).
- Alignment implemented with SentenceTransformers sentence-transformers/paraphrase-multilingual-mpnet-base-v2, version 2.2.2, cosine similarity ≥ 0.65, mutual nearest-neighbour matching, and an RG word-count ratio filter ≤ 1.3×.
- Translations were then scored by Qwen2-32B-Instruct (Qwen/Qwen2-32B-Instruct), deployed by the Swiss AI Initiative, using a strict integer-only evaluation prompt (0 for failures, otherwise 1–10 for accuracy + fluency).
- Only translations with a score ≥ 7 were retained.

File overview and counts

File	Task	Direction / Labels	# Examples
`sft_dictionary_RG.jsonl`	Dictionary list translation	de → Rumantsch Grischun: 7,132; Rumantsch Grischun → de: 7,132	14,264
`sft_dictionary_Surmiran.jsonl`	Dictionary list translation	de → Surmiran: 3,743; Surmiran → de: 3,743	7,486
`sft_dictionary_Sursilvan.jsonl`	Dictionary list translation	de → Sursilvan: 676; Sursilvan → de: 676	1,352
`sft_dictionary_Sutsilvan.jsonl`	Dictionary list translation	de → Sutsilvan: 2,927; Sutsilvan → de: 2,927	5,854
`sft_grischun_quality_filtered.jsonl`	Sentence translation (filtered)	German ↔ RG: 234; English ↔ RG: 262; French ↔ RG: 276; Italian ↔ RG: 266	1,038
`sft_surmiran_quality_filtered.jsonl`	Sentence translation (filtered)	de ↔ Surmiran: 42	42
`sft_surmiran_translated.jsonl`	Sentence translation	de ↔ Surmiran: 156	156
`sft_Sursilvan_quality_filtered.jsonl`	Sentence translation (filtered)	de ↔ Sursilvan: 44; Sursilvan ↔ de: 138	182
`sft_vallader_quality_filtered.jsonl`	Sentence translation (filtered)	de ↔ Vallader: 88	88
`sft_idiom_identification.jsonl`	Single-label classification	RG: 3,000; Sursilvan: 3,000; Surmiran: 3,000; Vallader: 3,000; Puter: 3,000; Sutsilvan: 1,322	16,322
`SFT_Human.jsonl`	Human-authored Romansh instructions	Free-form (Q&A, explanations, creative)	139

Acknowledgements

Thanks to volunteer translators—especially Donat D., Lea B., and Madlaina F. —and to Prof. Antoine Bosselut for prize support.

Contact

Note that all data has been preprocessed using the pipeline in https://github.com/swiss-ai/Swiss-AI-Romansh-Scripts. Questions or corrections: niklasc@icloud.com

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