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metadata 
configs:
  - config_name: bm25
    data_files:
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      - split: bn
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      - split: ko
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      - split: ru
        path: bm25/ru-*
      - split: sw
        path: bm25/sw-*
      - split: te
        path: bm25/te-*
      - split: th
        path: bm25/th-*
      - split: yo
        path: bm25/yo-*
      - split: zh
        path: bm25/zh-*
  - config_name: corpus
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      - split: bn
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      - split: de
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      - split: en
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      - split: es
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      - split: fi
        path: corpus/fi-*
      - split: fr
        path: corpus/fr-*
      - split: hi
        path: corpus/hi-*
      - split: id
        path: corpus/id-*
      - split: ja
        path: corpus/ja-*
      - split: ko
        path: corpus/ko-*
      - split: ru
        path: corpus/ru-*
      - split: sw
        path: corpus/sw-*
      - split: te
        path: corpus/te-*
      - split: th
        path: corpus/th-*
      - split: yo
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      - split: zh
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  - config_name: qrels
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      - split: bn
        path: qrels/bn-*
      - split: de
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      - split: es
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      - split: fa
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      - split: fi
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      - split: fr
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      - split: ru
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      - split: sw
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      - split: te
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      - split: th
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      - split: yo
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      - split: zh
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  - 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
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      - split: fa
        path: queries/fa-*
      - split: fi
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      - split: fr
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      - split: hi
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      - split: ja
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      - split: ko
        path: queries/ko-*
      - split: ru
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      - split: sw
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      - split: te
        path: queries/te-*
      - split: th
        path: queries/th-*
      - split: yo
        path: queries/yo-*
      - split: zh
        path: queries/zh-*
license: other
dataset_info:
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    dataset_size: 70201

🚧 This dataset is currently under construction. Specifications may change.

NanoMIRACL (with bm25 subset)

A lightweight, evaluation-ready subset of MIRACL, designed for fast multilingual IR benchmarking.

What this dataset is

  • A multilingual IR benchmark with 18 language splits: ar, bn, de, en, es, fa, fi, fr, hi, id, ja, ko, ru, sw, te, th, yo, zh.
  • Each split contains 50 queries and a corpus of 10,000 documents.
  • Built with deterministic sampling for reproducible benchmarking.

Data structure

  • corpus: _id, text
  • queries: _id, text
  • qrels: query-id, corpus-id, score
  • bm25: query-id, corpus-ids (A bm25 subset is included for first-stage retrieval and reranking experiments.)

Performance Comparison Across Models

Model avg ar bn de en es fa fi fr hi id ja ko ru sw te th yo zh
bm25 0.5138 0.5363 0.4760 0.4724 0.5831 0.5582 0.4837 0.6503 0.4241 0.5988 0.5178 0.5569 0.4627 0.4829 0.4472 0.5884 0.5798 0.4664 0.3632
e5-small 0.7181 0.7463 0.7127 0.6579 0.6968 0.7278 0.7203 0.7808 0.6339 0.6612 0.6261 0.7044 0.6730 0.7271 0.7025 0.9779 0.8896 0.6130 0.6737
e5-large 0.7791 0.8186 0.7920 0.7925 0.7386 0.8026 0.7522 0.8347 0.6710 0.7586 0.6229 0.7449 0.6907 0.7927 0.7540 0.9779 0.9174 0.8168 0.7465
bge-m3 0.7873 0.8193 0.8417 0.7337 0.7406 0.7419 0.7733 0.7977 0.7355 0.7402 0.6636 0.7975 0.7266 0.7993 0.7635 0.9926 0.9090 0.8547 0.7402

Subset names

  • Split names: ar, bn, de, en, es, fa, fi, fr, hi, id, ja, ko, ru, sw, te, th, yo, zh
  • Config names: corpus, queries, qrels, bm25

BM25 tokenization strategy

  • bm25 was generated with --auto-select-best-splitter.
  • Candidate strategies: transformer, stemmer, wordseg, nltk_stem, nltk_stem_stop, english_regex, english_porter, english_porter_stop, whitespace.
  • Selection metric: best nDCG@100 per split.

Selected strategy by split:

Split Strategy Details
ar nltk_stem NLTK stemmer
bn whitespace str.split()
de nltk_stem_stop NLTK stemmer + stopword removal
en english_regex regex tokenization (no stemming)
es nltk_stem NLTK stemmer
fa whitespace str.split()
fi nltk_stem_stop NLTK stemmer + stopword removal
fr nltk_stem_stop NLTK stemmer + stopword removal
hi stemmer PyStemmer (hindi)
id transformer tokenizer: Qwen/Qwen3-0.6B
ja wordseg ja (fugashi + unidic-lite)
ko transformer tokenizer: Qwen/Qwen3-0.6B
ru nltk_stem NLTK stemmer
sw whitespace str.split()
te whitespace str.split()
th wordseg th (pythainlp newmm)
yo transformer tokenizer: Qwen/Qwen3-0.6B
zh transformer tokenizer: Qwen/Qwen3-0.6B

Upstream source

License

Other. This dataset is derived from MIRACL and follows upstream licensing and attribution requirements.