metadata
configs:
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data_files:
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path: bm25/de-*
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path: bm25/es-*
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path: bm25/fr-*
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path: bm25/hi-*
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path: bm25/id-*
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path: bm25/ja-*
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path: bm25/ko-*
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path: bm25/ru-*
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path: bm25/sw-*
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path: bm25/te-*
- split: th
path: bm25/th-*
- split: yo
path: bm25/yo-*
- split: zh
path: bm25/zh-*
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data_files:
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path: corpus/ar-*
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path: corpus/bn-*
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path: corpus/de-*
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path: corpus/en-*
- split: es
path: corpus/es-*
- split: fa
path: corpus/fa-*
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path: corpus/fi-*
- split: fr
path: corpus/fr-*
- split: hi
path: corpus/hi-*
- split: id
path: corpus/id-*
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path: corpus/ja-*
- split: ko
path: corpus/ko-*
- split: ru
path: corpus/ru-*
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path: corpus/sw-*
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path: corpus/te-*
- split: th
path: corpus/th-*
- split: yo
path: corpus/yo-*
- split: zh
path: corpus/zh-*
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data_files:
- split: ar
path: qrels/ar-*
- split: bn
path: qrels/bn-*
- split: de
path: qrels/de-*
- split: en
path: qrels/en-*
- split: es
path: qrels/es-*
- split: fa
path: qrels/fa-*
- split: fi
path: qrels/fi-*
- split: fr
path: qrels/fr-*
- split: hi
path: qrels/hi-*
- split: id
path: qrels/id-*
- split: ja
path: qrels/ja-*
- split: ko
path: qrels/ko-*
- split: ru
path: qrels/ru-*
- split: sw
path: qrels/sw-*
- split: te
path: qrels/te-*
- split: th
path: qrels/th-*
- split: yo
path: qrels/yo-*
- split: zh
path: qrels/zh-*
- config_name: queries
data_files:
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path: queries/ar-*
- split: bn
path: queries/bn-*
- split: de
path: queries/de-*
- split: en
path: queries/en-*
- split: es
path: queries/es-*
- split: fa
path: queries/fa-*
- split: fi
path: queries/fi-*
- split: fr
path: queries/fr-*
- split: hi
path: queries/hi-*
- split: id
path: queries/id-*
- split: ja
path: queries/ja-*
- split: ko
path: queries/ko-*
- split: ru
path: queries/ru-*
- split: sw
path: queries/sw-*
- split: te
path: queries/te-*
- split: th
path: queries/th-*
- split: yo
path: queries/yo-*
- split: zh
path: queries/zh-*
license: other
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NanoMIRACL
This dataset is a Nano-style retrieval dataset. Nano-series evaluation can be run easily with the HAKARI Benchmark.
NanoMIRACL is derived from hotchpotch/miracl-hf-unified. It follows the Hugging Face
Datasets layout convention used by
sentence-transformers/NanoBEIR-en:
each Nano split has separate corpus, queries, and qrels tables, and BM25
candidates are provided separately in a bm25 table. This layout follows
the NanoBEIR-style evaluation approach summarized in
NanoBEIR.
NanoMIRACL contains multilingual retrieval splits derived from hotchpotch/miracl-hf-unified. The testB query split is used when available, with a fallback recorded in split metadata when the requested split is not usable.
Source Links
Data Layout
This dataset uses four Hugging Face Datasets configs:
corpus: documents with_idandtextqueries: queries with_idandtextqrels: positive relevance labels withquery-idandcorpus-idbm25: BM25 candidate lists withquery-idandcorpus-ids
Each config has the same Nano split names. The exact parquet paths are defined in the dataset card metadata above. If a regenerated dataset uses a different schema, config name, path layout, or field name, revise this section before publishing the README.
Construction Steps
This dataset was built as follows. If the actual generation procedure differs, revise this section before publishing the README.
- For each selected query, one positive document is kept and negatives are sampled from that query's source negatives before corpus fill.
- Use hotchpotch/miracl-hf-unified as the upstream benchmark or dataset family.
- Load source datasets from
hotchpotch/miracl-hf-unified. - Use
testBqueries when usable, with recorded per-language fallback when necessary. - Create one Nano split for each selected source retrieval task.
- Keep up to 200 eligible queries per Nano split.
- Include all qrels-positive documents for the selected queries.
- Fill the corpus from source corpus order up to 10000 documents.
- Remove exact duplicate document text within each split. If a removed duplicate was referenced by qrels, rewrite qrels to the retained document id.
- Store corpus text in the generated document
textfield. - Generate BM25 top-100 candidates with
per-split autotokenization, or the per-split tokenizer shown below. - If a qrels-positive document is missing from the raw BM25 result, insert it into the final
bm25candidate list by replacing a tail non-positive candidate.
BM25 Subset Policy
The bm25 config is a candidate subset for first-stage retrieval and reranking.
It is not a separate source dataset. Each row contains one query id and a ranked
list of up to 100 corpus ids.
BM25 candidates are generated from the selected corpus for each split. When a qrels-positive document is not present in the raw BM25 top-100 results, the missing positive is forced into the final candidate list by replacing a tail candidate that is not positive for that query. Candidate ids are kept unique after replacement.
Split Mapping
| Nano split | Source task | Source dataset | Queries | Corpus | Qrels |
|---|---|---|---|---|---|
ar |
ar_queries | hotchpotch/miracl-hf-unified | 200 | 1854 | 200 |
bn |
bn_queries | hotchpotch/miracl-hf-unified | 200 | 1731 | 200 |
de |
de_queries | hotchpotch/miracl-hf-unified | 200 | 1748 | 200 |
en |
en_queries | hotchpotch/miracl-hf-unified | 200 | 1657 | 200 |
es |
es_queries | hotchpotch/miracl-hf-unified | 200 | 1312 | 200 |
fa |
fa_queries | hotchpotch/miracl-hf-unified | 200 | 1858 | 200 |
fi |
fi_queries | hotchpotch/miracl-hf-unified | 200 | 1828 | 200 |
fr |
fr_queries | hotchpotch/miracl-hf-unified | 200 | 1777 | 200 |
hi |
hi_queries | hotchpotch/miracl-hf-unified | 200 | 1748 | 200 |
id |
id_queries | hotchpotch/miracl-hf-unified | 200 | 1520 | 200 |
ja |
ja_queries | hotchpotch/miracl-hf-unified | 200 | 1846 | 200 |
ko |
ko_queries | hotchpotch/miracl-hf-unified | 200 | 2419 | 200 |
ru |
ru_queries | hotchpotch/miracl-hf-unified | 200 | 1727 | 200 |
sw |
sw_queries | hotchpotch/miracl-hf-unified | 200 | 1600 | 200 |
te |
te_queries | hotchpotch/miracl-hf-unified | 84 | 754 | 84 |
th |
th_queries | hotchpotch/miracl-hf-unified | 200 | 1897 | 200 |
yo |
yo_queries | hotchpotch/miracl-hf-unified | 119 | 921 | 119 |
zh |
zh_queries | hotchpotch/miracl-hf-unified | 200 | 1700 | 200 |
BM25 nDCG@10
nDCG@10 is computed from the included BM25 ranking against the included qrels.
| Nano split | Tokenizer | Forced BM25 positives | BM25 nDCG@10 |
|---|---|---|---|
ar |
stemmer:ar/arabic |
19 | 0.5445 |
bn |
whitespace:bn |
9 | 0.5103 |
de |
stemmer:de/german |
39 | 0.3665 |
en |
stemmer:en/english |
6 | 0.5432 |
es |
stemmer:es/spanish |
16 | 0.5110 |
fa |
whitespace:fa |
9 | 0.5337 |
fi |
stemmer:fi/finnish |
14 | 0.6240 |
fr |
stemmer:fr/french |
55 | 0.3034 |
hi |
stemmer:hi/hindi |
6 | 0.5497 |
id |
stemmer:id/indonesian |
16 | 0.5705 |
ja |
wordseg:ja |
3 | 0.5956 |
ko |
wordseg:ko |
5 | 0.5090 |
ru |
stemmer:ru/russian |
31 | 0.4457 |
sw |
whitespace:sw |
9 | 0.5782 |
te |
whitespace:te |
8 | 0.6044 |
th |
wordseg:th |
7 | 0.6475 |
yo |
whitespace:yo |
13 | 0.5323 |
zh |
wordseg:zh |
18 | 0.4466 |
Skipped Tasks
None.
License
NanoMIRACL is a derived dataset. Users must comply with the licenses, terms, and attribution requirements of the upstream datasets listed above.