Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
parquet
Sub-tasks:
document-retrieval
Languages:
English
Size:
10K - 100K
License:
build ChatDoctorRetrieval from embedding-benchmark/ChatDoctor_HealthCareMagic@50c2986f · rteb_open v0.1.0
Browse files- README.md +84 -0
- corpus/test-00000-of-00001.parquet +3 -0
- provenance.json +140 -0
- qrels/test-00000-of-00001.parquet +3 -0
- queries/test-00000-of-00001.parquet +3 -0
README.md
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---
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pretty_name: RTEB · ChatDoctorRetrieval
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license: other
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license_name: unspecified-upstream
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language:
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- en
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multilinguality:
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- monolingual
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task_categories:
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- text-retrieval
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task_ids:
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- document-retrieval
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tags:
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- rteb
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- mteb
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- retrieval
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- healthcare
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configs:
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- config_name: corpus
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data_files:
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- split: test
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path: corpus/test-*.parquet
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- config_name: qrels
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data_files:
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- split: test
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path: qrels/test-*.parquet
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- config_name: queries
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data_files:
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- split: test
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path: queries/test-*.parquet
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---
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# ChatDoctorRetrieval — RTEB open subset, unified schema
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A normalised copy of the dataset behind the `mteb` task **`ChatDoctorRetrieval`**, one of the 17 open tasks in the
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[RTEB(beta)](https://huggingface.co/blog/rteb) retrieval benchmark. Same queries, documents and relevance
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judgements as the benchmark evaluates — reshaped into one strict schema shared by all 17.
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| | |
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|---|---|
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| Source | [`embedding-benchmark/ChatDoctor_HealthCareMagic`](https://huggingface.co/datasets/embedding-benchmark/ChatDoctor_HealthCareMagic/tree/50c2986fedffa33b38afd5c1752026f8e9e5ed1d) @ `50c2986fedff` (the revision pinned in `mteb`) |
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| Domain · languages | healthcare · eng |
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| Queries / documents / qrels | 5,591 / 5,545 / 5,591 |
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| Qrels per query | min 1 · mean 1.0 · max 1 |
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| Score values | 1 ×5,591 |
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| Layout | `queries` · `corpus` · `qrels`, split `test` |
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| License | `unspecified` |
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## Schema
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| config | columns | rules |
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|---|---|---|
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| `queries` | `id: string`, `text: string` | ids unique and non-empty; every query has ≥ 1 qrel |
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| `corpus` | `id: string`, `title: string`, `text: string` | `title` is always present (`""` when the source has none) |
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| `qrels` | `query-id: string`, `corpus-id: string`, `score: int32` | referential integrity to both tables; no duplicate pairs; no floats |
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Files are Parquet, sorted by id, zstd-compressed, sharded at 500 MB. Every rule above is enforced by a validator
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before publishing; `provenance.json` records the source file hashes, what changed, and the output file hashes.
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## What changed from the source
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- added a `title` column filled with `""` (the source has none)
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- cast `qrels.score` double -> int32
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- removed NUL bytes from text (prose dataset)
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- renamed `_id` → `id`
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- renamed source splits (`queries`←`queries/queries`, `corpus`←`corpus/corpus`, `qrels`←`default/test`) to `test`
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## Load it
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```python
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from datasets import load_dataset
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queries = load_dataset("Hyukkyu/rteb-ChatDoctorRetrieval", "queries", split="test")
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| 72 |
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corpus = load_dataset("Hyukkyu/rteb-ChatDoctorRetrieval", "corpus", split="test")
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qrels = load_dataset("Hyukkyu/rteb-ChatDoctorRetrieval", "qrels", split="test")
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```
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## License and attribution
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The data is redistributed under the source's terms — `unspecified`. All credit belongs to the
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original authors; see the source repository and the references in `mteb`'s task metadata (https://huggingface.co/datasets/embedding-benchmark/ChatDoctor_HealthCareMagic).
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This repository is an independent repackaging and is not affiliated with the RTEB or MTEB maintainers.
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> **License discrepancy.** The upstream dataset card declares `no license` while `mteb`'s `TaskMetadata` declares `not specified`. This card carries the upstream value as the more conservative choice.
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> **No license declared upstream.** Neither the source repo nor its origin states redistribution terms. This copy is published for reproducibility of the RTEB benchmark only; check with the original authors before any other use.
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corpus/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:7615469e2c5ebbb9c16b23f9e3c744c6bed4e0821c82a03b823da34ba790a04a
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size 1253932
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provenance.json
ADDED
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| 1 |
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{
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| 2 |
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"task": "ChatDoctorRetrieval",
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| 3 |
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"repo": "rteb-ChatDoctorRetrieval",
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| 4 |
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"rteb_open_version": "0.1.0",
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| 5 |
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"source": {
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| 6 |
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"path": "embedding-benchmark/ChatDoctor_HealthCareMagic",
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| 7 |
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"revision": "50c2986fedffa33b38afd5c1752026f8e9e5ed1d",
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| 8 |
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"url": "https://huggingface.co/datasets/embedding-benchmark/ChatDoctor_HealthCareMagic/tree/50c2986fedffa33b38afd5c1752026f8e9e5ed1d"
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| 9 |
+
},
|
| 10 |
+
"license": {
|
| 11 |
+
"card": null,
|
| 12 |
+
"mteb_task_metadata": "not specified",
|
| 13 |
+
"upstream_checked": true
|
| 14 |
+
},
|
| 15 |
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"languages": [
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| 16 |
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"eng"
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| 17 |
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],
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| 18 |
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"domain": "healthcare",
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| 19 |
+
"byte_preserving_text": false,
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| 20 |
+
"layout": {
|
| 21 |
+
"subsets": null,
|
| 22 |
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"splits": [
|
| 23 |
+
"test"
|
| 24 |
+
]
|
| 25 |
+
},
|
| 26 |
+
"parts": [
|
| 27 |
+
{
|
| 28 |
+
"subset": null,
|
| 29 |
+
"split": "test",
|
| 30 |
+
"source_configs": {
|
| 31 |
+
"queries": "queries/queries",
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| 32 |
+
"corpus": "corpus/corpus",
|
| 33 |
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"qrels": "default/test"
|
| 34 |
+
},
|
| 35 |
+
"normalize": {
|
| 36 |
+
"dropped_columns": {},
|
| 37 |
+
"orphan_queries_dropped": 0,
|
| 38 |
+
"duplicate_qrels_collapsed": 0,
|
| 39 |
+
"null_titles_filled": 0,
|
| 40 |
+
"score_cast": "double -> int32",
|
| 41 |
+
"id_renamed": true,
|
| 42 |
+
"title_added": true
|
| 43 |
+
},
|
| 44 |
+
"stats": {
|
| 45 |
+
"n_queries": 5591,
|
| 46 |
+
"n_corpus": 5545,
|
| 47 |
+
"n_qrels": 5591,
|
| 48 |
+
"qrels_per_query": {
|
| 49 |
+
"min": 1,
|
| 50 |
+
"mean": 1.0,
|
| 51 |
+
"max": 1
|
| 52 |
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},
|
| 53 |
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"score_values": {
|
| 54 |
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"1": 5591
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| 55 |
+
},
|
| 56 |
+
"dangling_qrels": 0,
|
| 57 |
+
"corpus_with_title": 0,
|
| 58 |
+
"avg_query_chars": 425.3,
|
| 59 |
+
"avg_doc_chars": 605.1
|
| 60 |
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}
|
| 61 |
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}
|
| 62 |
+
],
|
| 63 |
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"files": {
|
| 64 |
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"queries": {
|
| 65 |
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"test": [
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| 66 |
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{
|
| 67 |
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"path": "queries/test-00000-of-00001.parquet",
|
| 68 |
+
"rows": 5591,
|
| 69 |
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"bytes": 1059802,
|
| 70 |
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"sha256": "5a04065ceef7b324d30e0acd639051f6f43ebf46372519211d25c8650f1d18e3"
|
| 71 |
+
}
|
| 72 |
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]
|
| 73 |
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},
|
| 74 |
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"corpus": {
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| 75 |
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"test": [
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| 76 |
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{
|
| 77 |
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"path": "corpus/test-00000-of-00001.parquet",
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| 78 |
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"rows": 5545,
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| 79 |
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"bytes": 1253932,
|
| 80 |
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"sha256": "7615469e2c5ebbb9c16b23f9e3c744c6bed4e0821c82a03b823da34ba790a04a"
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| 81 |
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}
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| 82 |
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]
|
| 83 |
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},
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| 84 |
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"qrels": {
|
| 85 |
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"test": [
|
| 86 |
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{
|
| 87 |
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"path": "qrels/test-00000-of-00001.parquet",
|
| 88 |
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"rows": 5591,
|
| 89 |
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"bytes": 24895,
|
| 90 |
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"sha256": "73ab8ee73ca16ad80bb3204f18057bc086e5b473f0c7d3164f1a0beb62635e38"
|
| 91 |
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}
|
| 92 |
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]
|
| 93 |
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}
|
| 94 |
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},
|
| 95 |
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"stats_total": {
|
| 96 |
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"n_queries": 5591,
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| 97 |
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"n_corpus": 5545,
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| 98 |
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"n_qrels": 5591
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| 99 |
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},
|
| 100 |
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"source_files": [
|
| 101 |
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{
|
| 102 |
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"path": ".gitattributes",
|
| 103 |
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"size": 2461,
|
| 104 |
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"sha256": null,
|
| 105 |
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"blob_id": "1ef325f1b111266a6b26e0196871bd78baa8c2f3"
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},
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{
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"path": "README.md",
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| 109 |
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"size": 1567,
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| 110 |
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"sha256": null,
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"blob_id": "a7985658adf974d474cc9557c5870b41fd79c999"
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},
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{
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| 114 |
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"path": "corpus.jsonl",
|
| 115 |
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"size": 3538870,
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| 116 |
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"sha256": null,
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| 117 |
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"blob_id": "9baf880cf5475320f1bc431cd3f713d4228f91ff"
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},
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{
|
| 120 |
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"path": "queries.jsonl",
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"size": 2540397,
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| 123 |
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"blob_id": "bcbae8c657c6d449af1224695c854424280b4ccc"
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| 124 |
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},
|
| 125 |
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{
|
| 126 |
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"path": "relevance.jsonl",
|
| 127 |
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"size": 335460,
|
| 128 |
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"sha256": null,
|
| 129 |
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"blob_id": "69dfbe6c94f28be9672641d73d0934d893833aa5"
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| 130 |
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}
|
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],
|
| 132 |
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"build": {
|
| 133 |
+
"timestamp_utc": "2026-09-08T02:32:48Z",
|
| 134 |
+
"seconds": 7.6,
|
| 135 |
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"python": "3.11.0",
|
| 136 |
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"pyarrow": "25.0.1",
|
| 137 |
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"datasets": "5.0.1",
|
| 138 |
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"polars": "1.44.1"
|
| 139 |
+
}
|
| 140 |
+
}
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qrels/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:73ab8ee73ca16ad80bb3204f18057bc086e5b473f0c7d3164f1a0beb62635e38
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size 24895
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queries/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a04065ceef7b324d30e0acd639051f6f43ebf46372519211d25c8650f1d18e3
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size 1059802
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