Restore NanoNFCorpus full qrels and rebuild candidates

README.md

@@ -209,7 +209,7 @@ dataset_info:
     num_bytes: 274039
     num_examples: 50
   - name: NanoNFCorpus
-    num_bytes: 300155
+    num_bytes: 300134
     num_examples: 50
   - name: NanoNQ
     num_bytes: 334792
@@ -353,8 +353,8 @@ dataset_info:
     num_bytes: 1065
     num_examples: 50
   - name: NanoNFCorpus
-    num_bytes: 42309
-    num_examples: 1651
+    num_bytes: 64851
+    num_examples: 2518
   - name: NanoNQ
     num_bytes: 1340
     num_examples: 57
@@ -449,7 +449,7 @@ dataset_info:
     num_bytes: 55157
     num_examples: 50
   - name: NanoNFCorpus
-    num_bytes: 60625
+    num_bytes: 60573
     num_examples: 50
   - name: NanoNQ
     num_bytes: 67868
@@ -500,15 +500,15 @@ This dataset uses six Hugging Face Datasets configs:
 - `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.
+Each config has the same Nano split names. `NanoNFCorpus` includes the full positive qrels (2,518 rows); qrels are not capped to the top-100 reranking depth.
 
 ## 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`.
+- `bm25`: local BM25 top-500 with automatic tokenizer selection. Auto mode uses `wordseg` for `ja`, `zh`, `th`, `ko`, and `vi`, and `regex` otherwise. The resolved tokenizer is shown for each split in the Candidate Quality table.
 - `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.
+Safeguard means rank 101 is appended only when RRF top-100 contains no qrels-positive document. Qrels are not capped to fit the top-100 reranking depth. For `NanoNFCorpus`, some queries have more than 100 positive qrels, so top-100 hybrid candidate coverage is expected to be below 100%; this is a candidate-list diagnostic, not a qrels filtering rule.
 
 ## Split Statistics
 
@@ -523,7 +523,7 @@ Length statistics are character counts computed with `len(str(text))`.
 | NanoFiQA2018 | 50 | 4598 | 123 | 58.5 | 55.0 | 75.2 | 899.6 | 651.0 | 1136.8 |
 | NanoHotpotQA | 50 | 5090 | 100 | 88.3 | 82.5 | 107.0 | 349.6 | 299.0 | 479.0 |
 | NanoMSMARCO | 50 | 5043 | 50 | 32.2 | 29.0 | 40.0 | 330.2 | 298.0 | 380.0 |
-| NanoNFCorpus | 50 | 2953 | 1651 | 21.0 | 16.5 | 31.5 | 1512.7 | 1532.0 | 1775.0 |
+| NanoNFCorpus | 50 | 2953 | 2518 | 21.0 | 16.5 | 31.5 | 1512.7 | 1532.0 | 1775.0 |
 | NanoNQ | 50 | 5035 | 57 | 47.0 | 42.5 | 53.0 | 525.6 | 443.0 | 758.0 |
 | NanoQuoraRetrieval | 50 | 5046 | 70 | 48.0 | 43.5 | 54.8 | 54.8 | 47.0 | 64.0 |
 | NanoSCIDOCS | 50 | 2210 | 244 | 72.8 | 71.5 | 81.8 | 923.6 | 910.5 | 1230.5 |
@@ -538,7 +538,7 @@ Dense means `microsoft/harrier-oss-v1-270m` with the `web_search_query` prompt a
 
 | 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 | 60.86 | 61.52 | 81.65 | 84.36 | 86.27 | - | 14 |
+| Mean | - | 57.34 | 61.06 | 61.80 | 81.58 | 84.35 | 86.43 | - | 13 |
 | NanoArguAna | english_porter_stop | 46.50 | 57.87 | 54.22 | 100.00 | 94.00 | 100.00 | 100 | 0 |
 | NanoClimateFEVER | english_porter_stop | 32.66 | 28.11 | 34.19 | 60.50 | 72.83 | 74.33 | 100-101 | 1 |
 | NanoDBPedia | english_porter_stop | 63.74 | 62.43 | 65.64 | 77.87 | 79.94 | 85.56 | 100 | 0 |
@@ -546,7 +546,7 @@ Dense means `microsoft/harrier-oss-v1-270m` with the `web_search_query` prompt a
 | NanoFiQA2018 | english_porter_stop | 42.11 | 50.11 | 51.50 | 73.51 | 77.31 | 81.59 | 100-101 | 4 |
 | NanoHotpotQA | english_porter_stop | 82.70 | 80.43 | 83.25 | 96.00 | 91.00 | 97.00 | 100 | 0 |
 | NanoMSMARCO | english_porter_stop | 52.17 | 61.88 | 61.70 | 100.00 | 100.00 | 100.00 | 100 | 0 |
-| NanoNFCorpus | english_porter_stop | 30.60 | 31.35 | 31.78 | 21.05 | 30.58 | 29.69 | 100-101 | 6 |
+| NanoNFCorpus | regex@regex | 33.03 | 33.81 | 35.32 | 20.22 | 30.44 | 31.69 | 100-101 | 5 |
 | NanoNQ | english_porter_stop | 51.40 | 67.26 | 65.84 | 92.00 | 100.00 | 97.00 | 100-101 | 1 |
 | NanoQuoraRetrieval | english_porter_stop | 87.45 | 88.88 | 91.05 | 100.00 | 96.00 | 100.00 | 100 | 0 |
 | NanoSCIDOCS | english_porter_stop | 32.94 | 43.92 | 39.62 | 61.37 | 81.40 | 71.20 | 100-101 | 1 |
@@ -555,7 +555,7 @@ Dense means `microsoft/harrier-oss-v1-270m` with the `web_search_query` prompt a
 
 ## Hybrid Safeguard Summary
 
-- Safeguard positives: 14
+- Safeguard positives: 13
 - Rows limited by corpus size: 0
 - Metadata file: `reranking_hybrid_metadata.json`
 

bm25/NanoNFCorpus-00000-of-00001.parquet

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manifest.json

@@ -76,9 +76,9 @@
       "split_name": "NanoNFCorpus",
       "queries": 50,
       "corpus": 2953,
-      "qrels": 1651,
-      "forced_doc_count": 1391,
-      "bm25_ndcg_at_10": 0.3619835431487573,
+      "qrels": 2518,
+      "forced_doc_count": 1823,
+      "bm25_ndcg_at_10": 0.3302859919291999,
       "bm25_query_coverage": 1.0,
       "bm25_relevant_coverage": 1.0
     },

metadata/NanoNFCorpus.json

@@ -2,12 +2,14 @@
   "split_name": "NanoNFCorpus",
   "queries": 50,
   "corpus": 2953,
-  "qrels": 1651,
+  "qrels": 2518,
   "source_non_positive_qrels": 0,
   "qrels_selection": {
-    "qrels_per_query_cap": 100,
-    "removed_qrels_over_cap": 0,
-    "qrels_cap_policy": "positive qrels are capped per query to the BM25 candidate top_k"
+    "qrels_policy": "full positive qrels preserved",
+    "restored_qrels_from": "sentence-transformers/NanoBEIR-en@beb106fbcfaa599c508c667041bf8c85fd78736b",
+    "previous_hakari_qrels": 1651,
+    "restored_qrels": 867,
+    "max_positive_qrels_per_query": 463
   },
   "bm25": {
     "config": {
@@ -17,10 +19,10 @@
       "tokenizer": "regex",
       "tokenizer_name": null,
       "stemmer_algorithm": "english",
-      "top_k": 100,
+      "top_k": 500,
       "k1": 1.5,
       "b": 0.75,
-      "show_progress": true,
+      "show_progress": false,
       "auto_selected": true,
       "auto_detected_language": "en",
       "auto_detection_language_counts": {
@@ -28,21 +30,55 @@
       },
       "auto_detection_sample_size": 10
     },
-    "ndcg_at_10": 0.3619835431487573,
+    "ndcg_at_10": 0.3302859919291999,
+    "recall_at_100": 0.20223779487980484,
     "candidate_coverage": {
-      "top_k": 100,
+      "top_k": 500,
       "query_count": 50,
       "query_with_relevance_count": 50,
       "covered_query_count": 50,
       "query_coverage": 1.0,
-      "relevant_count": 1651,
-      "covered_relevant_count": 1651,
+      "relevant_count": 2518,
+      "covered_relevant_count": 2518,
       "relevant_coverage": 1.0
     },
-    "rebuild_policy": "BM25 candidates were recomputed locally and qrels-positive documents missing from the raw top-k were forced into the final candidate list.",
-    "forced_queries": 47,
-    "forced_doc_count": 1391,
+    "rebuild_policy": "BM25 top-500 was recomputed locally; full qrels were preserved; qrels-positive documents were forced into the top-500 candidate list when missing.",
+    "forced_queries": 46,
+    "forced_doc_count": 1823,
     "missing_positive_doc_count_after_forcing": 0,
-    "rebuilt_at_utc": "2026-05-19T01:30:09.912080+00:00"
+    "rebuilt_at_utc": "2026-06-07T22:40:13.006971+00:00"
+  },
+  "harrier_oss_v1_270m": {
+    "source": "copied from current hakari-bench dataset; dense top-500 is qrels-independent",
+    "ndcg_at_10": 0.33811016427765767,
+    "recall_at_100": 0.3043712120494943,
+    "candidate_coverage": {
+      "top_k": 500,
+      "query_count": 50,
+      "query_with_relevance_count": 50,
+      "covered_query_count": 48,
+      "query_coverage": 0.96,
+      "relevant_count": 2518,
+      "covered_relevant_count": 1077,
+      "relevant_coverage": 0.4277204130262113
+    }
+  },
+  "reranking_hybrid": {
+    "source": "rebuilt from BM25 top-500 and harrier_oss_v1_270m top-500 with RRF",
+    "rrf_k": 100,
+    "top_k": 100,
+    "ndcg_at_10": 0.3532276462667276,
+    "recall_at_100": 0.31688344735913987,
+    "candidate_coverage": {
+      "top_k": 100,
+      "query_count": 50,
+      "query_with_relevance_count": 50,
+      "covered_query_count": 45,
+      "query_coverage": 0.9,
+      "relevant_count": 2518,
+      "covered_relevant_count": 554,
+      "relevant_coverage": 0.2200158856235107
+    },
+    "safeguard_positive_count": 5
   }
 }

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