NanoMTEB-Scandinavian is a compact retrieval benchmark for Scandinavian-language MTEB-style task families. It includes Danish, Norwegian, and Swedish retrieval tasks spanning fact verification, question answering, news, encyclopedic content, FAQ retrieval, and social-media retrieval.

Usage

from datasets import load_dataset

dataset_id = "hakari-bench/NanoMTEB-Scandinavian"
split = "dan_fever"

queries = load_dataset(dataset_id, "queries", split=split)
corpus = load_dataset(dataset_id, "corpus", split=split)
qrels = load_dataset(dataset_id, "qrels", split=split)
reranking_candidates = load_dataset(dataset_id, "reranking_hybrid", split=split)

Data Layout

This dataset uses six Hugging Face Datasets configs:

corpus: documents with _id and text
queries: queries with _id and text
qrels: positive relevance labels with query-id and corpus-id
bm25: BM25 candidate lists with query-id and corpus-ids
harrier_oss_v1_270m: dense candidate lists from microsoft/harrier-oss-v1-270m
reranking_hybrid: RRF candidate lists built from bm25 and harrier_oss_v1_270m

Each config has the same Nano split names.

Candidate Construction

bm25: local BM25 top-500 with automatic language-aware tokenization. The resolved tokenizer is shown in the Candidate Quality table, for example wordseg@ja.
harrier_oss_v1_270m: dense top-500 from microsoft/harrier-oss-v1-270m. In tables this is shown as Dense; Dense means microsoft/harrier-oss-v1-270m with the web_search_query prompt for queries and cosine similarity over normalized embeddings.
reranking_hybrid: RRF over bm25 and harrier_oss_v1_270m using rrf_k=100, keeping the RRF top-100.

Safeguard means rank 101 is appended only when RRF top-100 contains no qrels-positive document.

Split Statistics

Length statistics are character counts computed with len(str(text)).

Nano split	Queries	Corpus	Qrels	Query chars avg	Query chars p50	Query chars p75	Doc chars avg	Doc chars p50	Doc chars p75
dan_fever	200	2522	200	59.5	55.0	74.0	312.2	249.0	421.0
nor_quad	196	1048	291	48.6	47.0	60.0	214.4	19.0	48.0
snl	200	1300	200	14.0	13.0	17.0	1986.9	1006.0	1907.5
swe_faq	200	511	200	73.3	65.0	91.0	319.8	263.0	408.5
swedn	200	2046	400	45.3	47.5	53.0	2896.0	916.5	5391.0
tv2_nordretrieval	200	2048	200	128.0	118.0	150.2	1440.7	1219.5	1886.2
twitter_hjerne	77	262	262	165.8	148.0	230.0	128.8	119.0	178.0

Candidate Quality

nDCG@10 and Recall@100 are computed from the included candidate rankings against the included qrels, then reported as 0-100 scores such as 52.45. Recall@100 uses only the top 100 candidates; an optional rank-101 safeguard positive is not counted in Recall@100.

Dense means microsoft/harrier-oss-v1-270m with the web_search_query prompt and cosine similarity.

Nano split	BM25 tokenizer	BM25 nDCG@10	Dense nDCG@10	Hybrid nDCG@10	BM25 Recall@100	Dense Recall@100	Hybrid Recall@100	Hybrid candidates	Safeguard positives
Mean	-	60.91	71.70	66.33	77.98	87.60	88.23	-	101
dan_fever	regex	88.56	86.30	88.32	100.00	97.00	100.00	100	0
nor_quad	regex	11.18	23.78	13.01	18.62	45.66	42.60	100-101	89
snl	regex	87.81	95.99	90.24	92.00	99.50	99.50	100-101	1
swe_faq	regex	54.49	64.88	63.95	90.50	94.00	96.50	100-101	7
swedn	regex	70.81	77.57	73.98	83.75	90.25	94.00	100-101	2
tv2_nordretrieval	regex	89.57	91.27	89.98	98.50	97.50	100.00	100	0
twitter_hjerne	regex	23.95	62.11	44.80	62.51	89.29	85.02	100-101	2

Hybrid Safeguard Summary

Safeguard positives: 101
Rows limited by corpus size: 0
Metadata file: reranking_hybrid_metadata.json

Source Links

License

NanoMTEB-Scandinavian is a derived dataset. Users must comply with the licenses, terms, and attribution requirements of the upstream MTEB task sources and their original datasets.

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