--- configs: - config_name: corpus data_files: - split: ar path: corpus/ar-00000-of-00001.parquet - split: bn path: corpus/bn-00000-of-00001.parquet - split: de path: corpus/de-00000-of-00001.parquet - split: en path: corpus/en-00000-of-00001.parquet - split: es path: corpus/es-00000-of-00001.parquet - split: fa path: corpus/fa-00000-of-00001.parquet - split: fi path: corpus/fi-00000-of-00001.parquet - split: fr path: corpus/fr-00000-of-00001.parquet - split: hi path: corpus/hi-00000-of-00001.parquet - split: id path: corpus/id-00000-of-00001.parquet - split: ja path: corpus/ja-00000-of-00001.parquet - split: ko path: corpus/ko-00000-of-00001.parquet - split: ru path: corpus/ru-00000-of-00001.parquet - split: sw path: corpus/sw-00000-of-00001.parquet - split: te path: corpus/te-00000-of-00001.parquet - split: th path: corpus/th-00000-of-00001.parquet - split: yo path: corpus/yo-00000-of-00001.parquet - split: zh path: corpus/zh-00000-of-00001.parquet - config_name: queries data_files: - split: ar path: queries/ar-00000-of-00001.parquet - split: bn path: queries/bn-00000-of-00001.parquet - split: de path: queries/de-00000-of-00001.parquet - split: en path: queries/en-00000-of-00001.parquet - split: es path: queries/es-00000-of-00001.parquet - split: fa path: queries/fa-00000-of-00001.parquet - split: fi path: queries/fi-00000-of-00001.parquet - split: fr path: queries/fr-00000-of-00001.parquet - split: hi path: queries/hi-00000-of-00001.parquet - split: id path: queries/id-00000-of-00001.parquet - split: ja path: queries/ja-00000-of-00001.parquet - split: ko path: queries/ko-00000-of-00001.parquet - split: ru path: queries/ru-00000-of-00001.parquet - split: sw path: queries/sw-00000-of-00001.parquet - split: te path: queries/te-00000-of-00001.parquet - split: th path: queries/th-00000-of-00001.parquet - split: yo path: queries/yo-00000-of-00001.parquet - split: zh path: queries/zh-00000-of-00001.parquet default: true - config_name: qrels data_files: - split: ar path: qrels/ar-00000-of-00001.parquet - split: bn path: qrels/bn-00000-of-00001.parquet - split: de path: qrels/de-00000-of-00001.parquet - split: en path: qrels/en-00000-of-00001.parquet - split: es path: qrels/es-00000-of-00001.parquet - split: fa path: qrels/fa-00000-of-00001.parquet - split: fi path: qrels/fi-00000-of-00001.parquet - split: fr path: qrels/fr-00000-of-00001.parquet - split: hi path: qrels/hi-00000-of-00001.parquet - split: id path: qrels/id-00000-of-00001.parquet - split: ja path: qrels/ja-00000-of-00001.parquet - split: ko path: qrels/ko-00000-of-00001.parquet - split: ru path: qrels/ru-00000-of-00001.parquet - split: sw path: qrels/sw-00000-of-00001.parquet - split: te path: qrels/te-00000-of-00001.parquet - split: th path: qrels/th-00000-of-00001.parquet - split: yo path: qrels/yo-00000-of-00001.parquet - split: zh path: qrels/zh-00000-of-00001.parquet - config_name: bm25 data_files: - split: ar path: bm25/ar-00000-of-00001.parquet - split: bn path: bm25/bn-00000-of-00001.parquet - split: de path: bm25/de-00000-of-00001.parquet - split: en path: bm25/en-00000-of-00001.parquet - split: es path: bm25/es-00000-of-00001.parquet - split: fa path: bm25/fa-00000-of-00001.parquet - split: fi path: bm25/fi-00000-of-00001.parquet - split: fr path: bm25/fr-00000-of-00001.parquet - split: hi path: bm25/hi-00000-of-00001.parquet - split: id path: bm25/id-00000-of-00001.parquet - split: ja path: bm25/ja-00000-of-00001.parquet - split: ko path: bm25/ko-00000-of-00001.parquet - split: ru path: bm25/ru-00000-of-00001.parquet - split: sw path: bm25/sw-00000-of-00001.parquet - split: te path: bm25/te-00000-of-00001.parquet - split: th path: bm25/th-00000-of-00001.parquet - split: yo path: bm25/yo-00000-of-00001.parquet - split: zh path: bm25/zh-00000-of-00001.parquet - config_name: harrier_oss_v1_270m data_files: - split: ar path: harrier_oss_v1_270m/ar-00000-of-00001.parquet - split: bn path: harrier_oss_v1_270m/bn-00000-of-00001.parquet - split: de path: harrier_oss_v1_270m/de-00000-of-00001.parquet - split: en path: harrier_oss_v1_270m/en-00000-of-00001.parquet - split: es path: harrier_oss_v1_270m/es-00000-of-00001.parquet - split: fa path: harrier_oss_v1_270m/fa-00000-of-00001.parquet - split: fi path: harrier_oss_v1_270m/fi-00000-of-00001.parquet - split: fr path: harrier_oss_v1_270m/fr-00000-of-00001.parquet - split: hi path: harrier_oss_v1_270m/hi-00000-of-00001.parquet - split: id path: harrier_oss_v1_270m/id-00000-of-00001.parquet - split: ja path: harrier_oss_v1_270m/ja-00000-of-00001.parquet - split: ko path: harrier_oss_v1_270m/ko-00000-of-00001.parquet - split: ru path: harrier_oss_v1_270m/ru-00000-of-00001.parquet - split: sw path: harrier_oss_v1_270m/sw-00000-of-00001.parquet - split: te path: harrier_oss_v1_270m/te-00000-of-00001.parquet - split: th path: harrier_oss_v1_270m/th-00000-of-00001.parquet - split: yo path: harrier_oss_v1_270m/yo-00000-of-00001.parquet - split: zh path: harrier_oss_v1_270m/zh-00000-of-00001.parquet - config_name: reranking_hybrid data_files: - split: ar path: reranking_hybrid/ar-00000-of-00001.parquet - split: bn path: reranking_hybrid/bn-00000-of-00001.parquet - split: de path: reranking_hybrid/de-00000-of-00001.parquet - split: en path: reranking_hybrid/en-00000-of-00001.parquet - split: es path: reranking_hybrid/es-00000-of-00001.parquet - split: fa path: reranking_hybrid/fa-00000-of-00001.parquet - split: fi path: reranking_hybrid/fi-00000-of-00001.parquet - split: fr path: reranking_hybrid/fr-00000-of-00001.parquet - split: hi path: reranking_hybrid/hi-00000-of-00001.parquet - split: id path: reranking_hybrid/id-00000-of-00001.parquet - split: ja path: reranking_hybrid/ja-00000-of-00001.parquet - split: ko path: reranking_hybrid/ko-00000-of-00001.parquet - split: ru path: reranking_hybrid/ru-00000-of-00001.parquet - split: sw path: reranking_hybrid/sw-00000-of-00001.parquet - split: te path: reranking_hybrid/te-00000-of-00001.parquet - split: th path: reranking_hybrid/th-00000-of-00001.parquet - split: yo path: reranking_hybrid/yo-00000-of-00001.parquet - split: zh path: reranking_hybrid/zh-00000-of-00001.parquet language: - ar - bn - de - en - es - fa - fi - fr - hi - id - ja - ko - ru - sw - te - th - yo - zh tags: - information-retrieval - retrieval - nano - bm25 - hakari-bench - dense-retrieval - reranking dataset_info: - config_name: bm25 features: - name: query-id dtype: string - name: corpus-ids list: string splits: - name: ar num_bytes: 1266611 num_examples: 200 - name: bn num_bytes: 1177519 num_examples: 200 - name: de num_bytes: 1298603 num_examples: 200 - name: en num_bytes: 1357970 num_examples: 200 - name: es num_bytes: 1288433 num_examples: 200 - name: fa num_bytes: 1262738 num_examples: 200 - name: fi num_bytes: 1218233 num_examples: 200 - name: fr num_bytes: 1309162 num_examples: 200 - name: hi num_bytes: 1208415 num_examples: 200 - name: id num_bytes: 1218449 num_examples: 200 - name: ja num_bytes: 1269008 num_examples: 200 - name: ko num_bytes: 1218171 num_examples: 200 - name: ru num_bytes: 1292152 num_examples: 200 - name: sw num_bytes: 1108061 num_examples: 200 - name: te num_bytes: 1161605 num_examples: 200 - name: th num_bytes: 1189537 num_examples: 200 - name: yo num_bytes: 657193 num_examples: 119 - name: zh num_bytes: 1263280 num_examples: 200 download_size: 21789444 dataset_size: 21765140 - config_name: corpus features: - name: _id dtype: string - name: text dtype: string splits: - name: ar num_bytes: 7174282 num_examples: 10000 - name: bn num_bytes: 12035077 num_examples: 10000 - name: de num_bytes: 4819401 num_examples: 10000 - name: en num_bytes: 4904869 num_examples: 10000 - name: es num_bytes: 4794294 num_examples: 10000 - name: fa num_bytes: 5768565 num_examples: 10000 - name: fi num_bytes: 4233118 num_examples: 10000 - name: fr num_bytes: 4151659 num_examples: 10000 - name: hi num_bytes: 10878177 num_examples: 10000 - name: id num_bytes: 4336884 num_examples: 10000 - name: ja num_bytes: 4982205 num_examples: 10000 - name: ko num_bytes: 4938423 num_examples: 10000 - name: ru num_bytes: 7807671 num_examples: 10000 - name: sw num_bytes: 2937176 num_examples: 10000 - name: te num_bytes: 10843968 num_examples: 10000 - name: th num_bytes: 11582202 num_examples: 10000 - name: yo num_bytes: 2330437 num_examples: 10000 - name: zh num_bytes: 3801244 num_examples: 10000 download_size: 59148256 dataset_size: 112319652 - config_name: harrier_oss_v1_270m features: - name: query-id dtype: string - name: corpus-ids list: string splits: - name: ar num_bytes: 1273629 num_examples: 200 - name: bn num_bytes: 1176065 num_examples: 200 - name: de num_bytes: 1301028 num_examples: 200 - name: en num_bytes: 1363247 num_examples: 200 - name: es num_bytes: 1294926 num_examples: 200 - name: fa num_bytes: 1262210 num_examples: 200 - name: fi num_bytes: 1218495 num_examples: 200 - name: fr num_bytes: 1311982 num_examples: 200 - name: hi num_bytes: 1207316 num_examples: 200 - name: id num_bytes: 1224728 num_examples: 200 - name: ja num_bytes: 1272296 num_examples: 200 - name: ko num_bytes: 1217697 num_examples: 200 - name: ru num_bytes: 1293929 num_examples: 200 - name: sw num_bytes: 1110175 num_examples: 200 - name: te num_bytes: 1159682 num_examples: 200 - name: th num_bytes: 1196182 num_examples: 200 - name: yo num_bytes: 655592 num_examples: 119 - name: zh num_bytes: 1268069 num_examples: 200 download_size: 21831454 dataset_size: 21807248 - config_name: qrels features: - name: query-id dtype: string - name: corpus-id dtype: string splits: - name: ar num_bytes: 7267 num_examples: 386 - name: bn num_bytes: 7436 num_examples: 407 - name: de num_bytes: 13650 num_examples: 538 - name: en num_bytes: 11324 num_examples: 560 - name: es num_bytes: 23740 num_examples: 934 - name: fa num_bytes: 10577 num_examples: 427 - name: fi num_bytes: 6081 num_examples: 328 - name: fr num_bytes: 10612 num_examples: 417 - name: hi num_bytes: 9654 num_examples: 410 - name: id num_bytes: 12133 num_examples: 654 - name: ja num_bytes: 7131 num_examples: 373 - name: ko num_bytes: 9572 num_examples: 508 - name: ru num_bytes: 10750 num_examples: 555 - name: sw num_bytes: 7188 num_examples: 405 - name: te num_bytes: 3855 num_examples: 211 - name: th num_bytes: 6309 num_examples: 343 - name: yo num_bytes: 3143 num_examples: 144 - name: zh num_bytes: 11666 num_examples: 471 download_size: 122826 dataset_size: 172088 - config_name: queries features: - name: _id dtype: string - name: text dtype: string splits: - name: ar num_bytes: 13271 num_examples: 200 - name: bn num_bytes: 27235 num_examples: 200 - name: de num_bytes: 12632 num_examples: 200 - name: en num_bytes: 10199 num_examples: 200 - name: es num_bytes: 13486 num_examples: 200 - name: fa num_bytes: 17958 num_examples: 200 - name: fi num_bytes: 9852 num_examples: 200 - name: fr num_bytes: 12361 num_examples: 200 - name: hi num_bytes: 31659 num_examples: 200 - name: id num_bytes: 9871 num_examples: 200 - name: ja num_bytes: 12505 num_examples: 200 - name: ko num_bytes: 13045 num_examples: 200 - name: ru num_bytes: 18950 num_examples: 200 - name: sw num_bytes: 9853 num_examples: 200 - name: te num_bytes: 22938 num_examples: 200 - name: th num_bytes: 27216 num_examples: 200 - name: yo num_bytes: 6697 num_examples: 119 - name: zh num_bytes: 9826 num_examples: 200 download_size: 183744 dataset_size: 279554 - config_name: reranking_hybrid features: - name: query-id dtype: string - name: corpus-ids list: string splits: - name: ar num_bytes: 253968 num_examples: 200 - name: bn num_bytes: 236250 num_examples: 200 - name: de num_bytes: 261001 num_examples: 200 - name: en num_bytes: 272500 num_examples: 200 - name: es num_bytes: 259586 num_examples: 200 - name: fa num_bytes: 253821 num_examples: 200 - name: fi num_bytes: 244186 num_examples: 200 - name: fr num_bytes: 263592 num_examples: 200 - name: hi num_bytes: 242989 num_examples: 200 - name: id num_bytes: 242548 num_examples: 200 - name: ja num_bytes: 254284 num_examples: 200 - name: ko num_bytes: 244095 num_examples: 200 - name: ru num_bytes: 259305 num_examples: 200 - name: sw num_bytes: 223021 num_examples: 200 - name: te num_bytes: 234272 num_examples: 200 - name: th num_bytes: 239389 num_examples: 200 - name: yo num_bytes: 132452 num_examples: 119 - name: zh num_bytes: 254917 num_examples: 200 download_size: 4393763 dataset_size: 4372176 --- # NanoMIRACL This dataset is a Nano-style retrieval dataset for [HAKARI-bench](https://github.com/hakari-bench/hakari-bench). NanoMIRACL is a compact multilingual benchmark derived from MIRACL. Each language split evaluates monolingual retrieval of Wikipedia passages for natural-language questions. This rebuild uses `hotchpotch/miracl-hf-unified` dev queries at source revision `21ad00eb467639e927b5badb7c49f4947c6c24ca`. For each sampled query, it preserves all source positive passages and expands the split-local corpus to 10,000 documents using source negatives as hard-negative candidates plus deterministic random fill. ## Usage ```python from datasets import load_dataset dataset_id = "hakari-bench/NanoMIRACL" split = "ar" 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 | |---|---:|---:|---:|---:|---:|---:|---:|---:|---:| | ar | 200 | 10000 | 386 | 30.1 | 27.0 | 35.0 | 392.3 | 276.0 | 520.0 | | bn | 200 | 10000 | 407 | 47.2 | 43.5 | 58.0 | 446.2 | 359.0 | 597.0 | | de | 200 | 10000 | 538 | 45.4 | 43.0 | 52.0 | 457.2 | 372.0 | 612.0 | | en | 200 | 10000 | 560 | 39.9 | 37.5 | 48.0 | 471.8 | 392.0 | 645.0 | | es | 200 | 10000 | 934 | 47.6 | 47.0 | 55.0 | 453.2 | 370.0 | 597.0 | | fa | 200 | 10000 | 427 | 40.0 | 38.0 | 46.0 | 310.7 | 213.0 | 413.0 | | fi | 200 | 10000 | 328 | 37.2 | 33.5 | 46.2 | 393.6 | 326.0 | 522.0 | | fr | 200 | 10000 | 417 | 43.3 | 43.0 | 51.0 | 385.3 | 296.0 | 513.0 | | hi | 200 | 10000 | 410 | 54.8 | 52.0 | 65.0 | 419.3 | 320.0 | 559.0 | | id | 200 | 10000 | 654 | 38.3 | 37.0 | 45.0 | 416.5 | 316.0 | 567.0 | | ja | 200 | 10000 | 373 | 17.5 | 17.0 | 21.0 | 173.4 | 135.0 | 231.0 | | ko | 200 | 10000 | 508 | 21.7 | 19.0 | 22.0 | 205.3 | 163.0 | 273.0 | | ru | 200 | 10000 | 555 | 45.5 | 41.0 | 53.5 | 423.3 | 313.0 | 569.0 | | sw | 200 | 10000 | 405 | 38.3 | 37.0 | 44.0 | 278.0 | 204.0 | 338.0 | | te | 200 | 10000 | 211 | 38.4 | 36.5 | 43.0 | 409.0 | 295.0 | 486.0 | | th | 200 | 10000 | 343 | 43.6 | 40.0 | 50.2 | 409.9 | 346.0 | 538.0 | | yo | 119 | 10000 | 144 | 37.7 | 36.0 | 42.0 | 176.7 | 81.0 | 187.0 | | zh | 200 | 10000 | 471 | 10.9 | 11.0 | 12.0 | 133.4 | 105.0 | 176.0 | ## 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 | - | 57.15 | 76.27 | 69.00 | 93.32 | 94.02 | 99.26 | - | 19 | | ar | stemmer@arabic | 63.52 | 82.23 | 75.14 | 97.40 | 96.58 | 99.83 | 100 | 0 | | bn | whitespace | 50.33 | 76.61 | 65.37 | 95.17 | 95.57 | 99.75 | 100 | 0 | | de | stemmer@german | 51.72 | 73.89 | 64.18 | 91.78 | 93.10 | 98.27 | 100-101 | 1 | | en | english_porter_stop | 67.74 | 77.21 | 74.74 | 99.38 | 95.00 | 99.75 | 100 | 0 | | es | stemmer@spanish | 68.61 | 77.93 | 74.78 | 98.06 | 93.31 | 100.00 | 100 | 0 | | fa | regex | 57.88 | 64.76 | 63.34 | 96.22 | 88.99 | 99.30 | 100-101 | 1 | | fi | stemmer@finnish | 77.34 | 86.34 | 83.32 | 98.58 | 95.42 | 100.00 | 100 | 0 | | fr | stemmer@french | 46.58 | 68.28 | 58.96 | 97.96 | 91.35 | 99.88 | 100 | 0 | | hi | stemmer@hindi | 30.37 | 68.47 | 51.74 | 70.18 | 91.99 | 96.00 | 100-101 | 7 | | id | stemmer@indonesian | 67.73 | 70.76 | 71.71 | 98.01 | 95.04 | 99.83 | 100 | 0 | | ja | wordseg@ja | 66.01 | 77.45 | 72.23 | 97.33 | 91.78 | 100.00 | 100 | 0 | | ko | wordseg@ko | 49.94 | 69.10 | 70.26 | 95.74 | 92.02 | 98.12 | 100-101 | 3 | | ru | stemmer@russian | 58.87 | 76.93 | 68.16 | 89.50 | 93.20 | 98.43 | 100-101 | 3 | | sw | regex | 58.52 | 78.72 | 72.92 | 94.89 | 94.95 | 99.75 | 100 | 0 | | te | whitespace | 52.92 | 87.20 | 69.53 | 87.92 | 92.50 | 98.25 | 100-101 | 3 | | th | wordseg@th | 62.29 | 81.01 | 72.96 | 95.58 | 95.25 | 99.50 | 100-101 | 1 | | yo | regex | 58.16 | 84.16 | 76.51 | 92.44 | 97.48 | 100.00 | 100 | 0 | | zh | wordseg@zh | 40.22 | 71.91 | 56.19 | 83.62 | 98.90 | 100.00 | 100 | 0 | ## Hybrid Safeguard Summary - Safeguard positives: 19 - Rows limited by corpus size: 0 - Metadata file: `reranking_hybrid_metadata.json` ## Source Links - [hotchpotch/miracl-hf-unified](https://huggingface.co/datasets/hotchpotch/miracl-hf-unified) - [miracl/miracl](https://huggingface.co/datasets/miracl/miracl) - [miracl/miracl-corpus](https://huggingface.co/datasets/miracl/miracl-corpus) ## License NanoMIRACL is a derived dataset. Users must comply with the licenses, terms, and attribution requirements of the upstream source datasets.