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configs:
- config_name: bm25
data_files:
- split: ar
path: bm25/ar-*
- split: bn
path: bm25/bn-*
- split: de
path: bm25/de-*
- split: en
path: bm25/en-*
- split: es
path: bm25/es-*
- split: fa
path: bm25/fa-*
- split: fi
path: bm25/fi-*
- split: fr
path: bm25/fr-*
- split: hi
path: bm25/hi-*
- split: id
path: bm25/id-*
- split: ja
path: bm25/ja-*
- split: ko
path: bm25/ko-*
- 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
data_files:
- split: ar
path: corpus/ar-*
- split: bn
path: corpus/bn-*
- split: de
path: corpus/de-*
- split: en
path: corpus/en-*
- split: es
path: corpus/es-*
- split: fa
path: corpus/fa-*
- 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
path: corpus/yo-*
- split: zh
path: corpus/zh-*
- config_name: qrels
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:
- split: ar
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
dataset_info:
- config_name: bm25
features:
- name: query-id
dtype: string
- name: corpus-ids
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---
🚧 This dataset is currently under construction. Specifications may change.
# NanoMIRACL (with bm25 subset)
A lightweight, evaluation-ready subset of [MIRACL](https://huggingface.co/datasets/miracl/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
- Original dataset: [MIRACL](https://huggingface.co/datasets/miracl/miracl)
- Base processed source: [hotchpotch/miracl-hf-unified](https://huggingface.co/datasets/hotchpotch/miracl-hf-unified)
## License
Other. This dataset is derived from MIRACL and follows upstream licensing and attribution requirements. |