da-instruct-dynaword-contemporary

Danish instruction fine-tuning dataset generated via backtranslation from danish-foundation-models/danish-dynaword, restricted to contemporary Danish subsets with no annotation-based quality filtering.

Subsets consisting primarily of historical or archaic Danish are excluded. See oliverkinch/da-instruct-dynaword-contemporary-hq for a version with additional quality filtering via dynaword-annotations.

Dataset description

Each row is a (prompt, target) pair where:

• target is a passage of authentic Danish text drawn from a curated subset of DynaWord
• prompt is a realistic Danish user instruction that would plausibly elicit that text from a language model

Prompts were generated by Qwen/Qwen3.5-397B-A17B using a backtranslation approach: given a passage and its source context, the model is asked to write the user message that would cause a chatbot to produce a similar text. Domain-specific prompt templates (government, literary, academic, tax guidance, news, speech) ensure that the generated instructions match the register and genre of the source text.

Construction

1 — Subset selection

Subsets consisting primarily of historical or archaic Danish were excluded, leaving 32 contemporary subsets. 10,000 IDs were randomly sampled without replacement from the full pool of IDs across these subsets. No annotation-based quality filter was applied.

2 — Passage extraction

Articles shorter than 400 characters were discarded. Longer articles were chunked into passages of up to 2,500 characters using a hybrid scoring approach (paragraph boundary detection with quality scoring). A maximum of 2 passages per article was kept.

Passage-level quality filters reject:

• OCR noise (inter-word double spaces, ligature splits, high mixed-alphanumeric token ratio)
• Repetitive content (unique word ratio < 28% or word run ≥ 6)
• Document colophons and mastheads (phone/email/ISSN markers in first 300 chars)
• YAML/markdown frontmatter

3 — Prompt generation

For each passage, Qwen3.5-397B-A17B was prompted with the passage text and source context metadata to generate a Danish user instruction. Six domain-specific system prompts were used:

• government — administrative and public information requests
• literary — prose, fiction, letters and historical texts
• academic — scholarly articles and analytical texts
• tax_guidance — practical citizen queries about tax rules
• speech — parliamentary speeches and public addresses
• news — news articles and encyclopedic texts (default)

Generated prompts were validated with rule-based filters: language detection (must be Danish), user-request detection (must include a question or imperative verb), shouting token check, roleplay pattern rejection, and prompt-target content overlap check.

4 — Results

8,271 instruction pairs generated from 10,000 randomly sampled source IDs across 32 dynaword subsets.

Source coverage

Subset	Domain	Source type	Pairs
wiki	encyclopedia	news	2,263
retsinformationdk	legal	government	1,567
ai-aktindsigt	government	government	1,242
nordjyllandnews	news	news	633
tv2r	news	news	451
cellar	EU documents	government	438
ncc_maalfrid	web/government	government	277
health_hovedstaden	health	government	236
opensubtitles	film/TV subtitles	literary	220
Domsdatabasen	legal	government	179
municipality_meetings	government	government	177
skat	tax	tax_guidance	115
hest	forum	news	90
tidsskrift-dk	journalism/academic	academic	53
wiki_misc	wiki comments	news	45
kb_administrative_publication	administrative	government	39
retspraksis	legal	government	38
ncc_books	books	literary	37
miljoeportalen	environment	government	36
wikibooks	educational	news	25
danske-taler	speeches	speech	24
ep	EU parliament	speech	20
eur-lex-sum-da	EU law	government	13
wikisource	books	literary	10
ft	parliament	speech	9
ncc_newspaper	news	news	9
depbank	linguistic corpus	literary	8
ncc_parliament	parliament	speech	7
fm-udgivelser	government	government	4
botxt	books	literary	2
naat	web	speech	2
nota	accessible library	literary	2

Schema

{
    "id": "backtranslation_passages_dynaword-<hash>",
    "prompt": "Danish user instruction (generated)",
    "target": "Danish text passage (from source corpus)",
    "meta": {
        "passage_idx": 0,                # passage index within the source article
        "source_config_name": "skat",    # HuggingFace config name
        "source_dataset": "danish-foundation-models/danish-dynaword",
        "source_id": "skat::SKM...",     # original article ID
        "source_key": "skat",
        "source_name": "skat",           # dynaword subset name
        "source_record_index": 42,
        "source_split": "train",
        "source_type": "tax_guidance",   # prompt template used
        "target_chars": 1842
    },
    "sources": [
        {"config_name": "skat", "dataset": "danish-foundation-models/danish-dynaword",
         "row_id": "skat::SKM...", "split": "train"}
    ]
}

Usage

from datasets import load_dataset

ds = load_dataset("oliverkinch/da-instruct-dynaword-contemporary")
# ds["train"]

# Format for SFT
def format_example(row):
    return {
        "messages": [
            {"role": "user",      "content": row["prompt"]},
            {"role": "assistant", "content": row["target"]},
        ]
    }

Licence

This dataset inherits the licences of the constituent DynaWord subsets. Subsets carry a range of open licences (CC0, CC-BY, CC-BY-SA, government open data). See the DynaWord dataset card for per-subset licence details.

The generated prompt column was produced with Qwen/Qwen3.5-397B-A17B and is released under CC-BY 4.0.

Related datasets

Dataset	Subsets	Quality filter	Pairs
oliverkinch/da-instruct-dynaword-contemporary	contemporary only	none	8,271
oliverkinch/da-instruct-dynaword-contemporary-hq	contemporary only	dynaword-annotations	11,303
oliverkinch/da-instruct-dynaword-hq	all 40 subsets	dynaword-annotations	10,660
oliverkinch/da-instruct-dynaword	all 40 subsets	dynaword-annotations	39,847

• danish-foundation-models/danish-dynaword — source corpus
• danish-foundation-models/dynaword-annotations — quality annotations