build ELI5 from sentence-transformers/eli5@6e3b20a7 · rteb_open v0.1.0

README.md

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+---
+pretty_name: Training · ELI5
+license: other
+license_name: unspecified-upstream
+language:
+- en
+multilinguality:
+- monolingual
+task_categories:
+- text-retrieval
+task_ids:
+- document-retrieval
+tags:
+- train
+- mteb
+- retrieval
+- long-form QA (Reddit)
+configs:
+- config_name: corpus
+  data_files:
+  - split: train
+    path: corpus/train-*.parquet
+- config_name: hard-negatives
+  data_files:
+  - split: train
+    path: hard-negatives/train-*.parquet
+- config_name: qrels
+  data_files:
+  - split: train
+    path: qrels/train-*.parquet
+- config_name: queries
+  data_files:
+  - split: train
+    path: queries/train-*.parquet
+- config_name: teacher-scores
+  data_files:
+  - split: train
+    path: teacher-scores/train-*.parquet
+---
+# ELI5 — Training, unified schema
+
+A normalised copy of the dataset behind the `mteb` task **`ELI5`**, a retrieval **training** set built from [`sentence-transformers/eli5`](https://huggingface.co/datasets/sentence-transformers/eli5). Same queries, documents
+and relevance judgements as the benchmark evaluates — reshaped into one strict schema shared by every dataset
+in this collection.
+
+|  |  |
+|---|---|
+| Source | [`sentence-transformers/eli5`](https://huggingface.co/datasets/sentence-transformers/eli5/tree/6e3b20a7a427560845779f217c3ff71493374bc0) @ `6e3b20a7a427` (the revision pinned in `mteb`) |
+| Domain · languages | long-form QA (Reddit) · eng |
+| Queries / documents / qrels | 323,136 / 325,293 / 325,473 |
+| Qrels per query | min 1 · mean 1.007 · max 110 |
+| Score values | 1 ×325,473 |
+| Layout | `queries` · `corpus` · `qrels` · `hard-negatives` · `teacher-scores`, split `train` |
+| Splits | `corpus`: train · `hard-negatives`: train · `qrels`: train · `queries`: train · `teacher-scores`: train |
+| Hard negatives | **none yet** — config present with 0 rows |
+| Teacher scores | **none yet** — config present with 0 rows |
+| Reading empty configs | `datasets` cannot return a 0-example split (`load_dataset` raises "corresponds to no data"); until rows exist, read the Parquet directly with `pyarrow`/`polars`/`pandas`. The schema is declared in the file and in `configs:` above |
+| Ids | `sha1(text)[:20]`; identical texts collapse to one document (182 collapsed) |
+| License | `unspecified` |
+
+## Schema
+
+| config | columns | rules |
+|---|---|---|
+| `queries` | `id: string`, `text: string` | ids unique and non-empty; every query has ≥ 1 qrel |
+| `corpus` | `id: string`, `title: string`, `text: string` | `title` is always present (`""` when the source has none) |
+| `qrels` | `query-id: string`, `corpus-id: string`, `score: int32` | referential integrity to both tables; no duplicate pairs; no floats |
+| `hard-negatives` | `query-id: string`, `corpus-id: string`, `rank: int32`, `source: string` | one row per mined negative; `(query-id, corpus-id, source)` unique; never a labelled positive of the same query |
+| `teacher-scores` | `query-id: string`, `corpus-id: string`, `teacher: string`, `score: float32` | one row per scored pair (positives included); a row *means* scored — never a placeholder |
+
+Files are Parquet, sorted by id, zstd-compressed, sharded at 500 MB. Every rule above is enforced by a validator
+before publishing; `provenance.json` records the source file hashes, what changed, and the output file hashes.
+
+## What changed from the source
+
+- **byte-preserved** all text — no whitespace, newline, or control-character normalisation
+
+## Load it
+
+```python
+from datasets import load_dataset
+queries = load_dataset("Hyukkyu/train-eli5", "queries", split="train")
+corpus  = load_dataset("Hyukkyu/train-eli5", "corpus", split="train")
+qrels   = load_dataset("Hyukkyu/train-eli5", "qrels", split="train")
+```
+
+## License and attribution
+
+The data is redistributed under the source's terms — `unspecified`. All credit belongs to the
+original authors; see the source repository and the references in `mteb`'s task metadata (https://huggingface.co/datasets/sentence-transformers/eli5).
+This repository is an independent repackaging and is not affiliated with the RTEB or MTEB maintainers.
+
+> **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.

corpus/train-00000-of-00001.parquet

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hard-negatives/train-00000-of-00001.parquet

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provenance.json

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+{
+ "task": "ELI5",
+ "benchmark": "train",
+ "repo": "train-eli5",
+ "rteb_open_version": "0.1.0",
+ "source": {
+  "path": "sentence-transformers/eli5",
+  "revision": "6e3b20a7a427560845779f217c3ff71493374bc0",
+  "url": "https://huggingface.co/datasets/sentence-transformers/eli5/tree/6e3b20a7a427560845779f217c3ff71493374bc0",
+  "configs": [
+   "pair/train"
+  ]
+ },
+ "license": {
+  "card": null,
+  "mteb_task_metadata": null,
+  "upstream_checked": true
+ },
+ "languages": [
+  "eng"
+ ],
+ "domain": "long-form QA (Reddit)",
+ "byte_preserving_text": true,
+ "symmetric": false,
+ "layout": {
+  "subsets": null,
+  "splits": [
+   "train"
+  ],
+  "split_map": null
+ },
+ "id_scheme": "sha1(text)[:20]",
+ "parts": [
+  {
+   "subset": null,
+   "split": "train",
+   "source_configs": {
+    "pairs": [
+     "pair/train"
+    ]
+   },
+   "normalize": {
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+    "title_added": false,
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+    "id_renamed": false,
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+    "duplicate_qrels_collapsed": 0,
+    "score_cast": null,
+    "negatives_that_were_positives_dropped": 0
+   },
+   "stats": {
+    "n_corpus": 325293,
+    "empty_docs": 0,
+    "duplicate_text_docs": 0,
+    "corpus_with_title": 0,
+    "avg_doc_chars": 439.2,
+    "text_rows_in_source": 325475,
+    "collapsed_duplicate_texts": 182,
+    "n_queries": 323136,
+    "n_qrels": 325473,
+    "qrels_per_query": {
+     "min": 1,
+     "mean": 1.007,
+     "max": 110
+    },
+    "score_values": {
+     "1": 325473
+    },
+    "dangling_qrels": 0,
+    "avg_query_chars": 85.3,
+    "n_hard_negatives": 0,
+    "sources": [],
+    "negatives_per_query": null,
+    "positives_among_negatives": 0,
+    "n_teacher_scores": 0,
+    "teachers": []
+   }
+  }
+ ],
+ "files": {
+  "corpus": {
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+     "rows": 325293,
+     "bytes": 67325645,
+     "sha256": "bbc8eb12595b71c90824ee61199565ff3d5e4cc591219af4673452584175fcdd"
+    }
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+  "queries": {
+   "train": [
+    {
+     "path": "queries/train-00000-of-00001.parquet",
+     "rows": 323136,
+     "bytes": 16759363,
+     "sha256": "2936ccdc07a76670733dcd696174dd75eeb3641835dfe5451ef7c8fc7b53b0d0"
+    }
+   ]
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+  "qrels": {
+   "train": [
+    {
+     "path": "qrels/train-00000-of-00001.parquet",
+     "rows": 325473,
+     "bytes": 7396847,
+     "sha256": "5829a23e5887c1dea2a47da81643648286d9ae70108b435149f9dd58fe02f8ba"
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+  "hard-negatives": {
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+    }
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+  },
+  "teacher-scores": {
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+     "path": "teacher-scores/train-00000-of-00001.parquet",
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+ "stats_total": {
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+  "n_corpus": 325293,
+  "n_qrels": 325473,
+  "n_hard_negatives": 0,
+  "n_teacher_scores": 0
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+ "availability": {
+  "hard_negatives": "none",
+  "teacher_scores": "none"
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+   "blob_id": "4eab387a95e764fbde022d5110ef7deab27564eb"
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+ "build": {
+  "timestamp_utc": "2026-09-08T08:52:20Z",
+  "seconds": 4.7,
+  "peak_rss_gb": 1.45,
+  "python": "3.11.0",
+  "pyarrow": "25.0.1",
+  "polars": "1.44.1"
+ }
+}

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