Training — unified schema
Collection
The 15 training sources in one strict schema across 13 repos: 9 pair sets, 3 DPR query sets on a shared corpus, 3 BEIR train splits. • 14 items • Updated
Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
parquet
Sub-tasks:
document-retrieval
Languages:
English
Size:
1M - 10M
License:
id stringlengths 20 20 | title stringclasses 1
value | text stringlengths 1 727 |
|---|---|---|
000016e80b1bd302a4e8 | There is still a grudge against him. | |
00002cc84c23058df628 | Legal service clients are a small group, composed mainly of white males. | |
0000373f0590c86c48ff | A kick is throwing a baby. | |
000053d8ea26febd941b | Two young people walk down a sidewalk in jackets. | |
000058908b3bc88524a0 | He hadn't taken into account where he was going to place the re-wrapped mummies. | |
000070f691a747c3d9b7 | Jon did not nod. | |
0000738a2568667d62ed | Industry conditions determine a companies benchmark points. | |
000087af7f4db92d3a1a | The person does not like to do winter sports. | |
00008d953ae240ddbeda | The old man is wearing a white cap | |
0000da4bb0faed8493b0 | Branding is the beginning of the end for a company. | |
0000eaa306ba74353513 | a boy sweeps floor | |
0000fda6afac18d0f0ff | He made it all the way through spring training without injury. | |
0000fec8f21eef39b818 | Relations were forged with the Sui dynasty in China too. | |
0001bc737a759e498fa8 | Somebody knew where they were. | |
0001eccea5eeb9ae9f12 | the workers were looking | |
0001fc98b2391834dc83 | The rock formations make a them look like castles. | |
00022b6ed9f7153ce672 | Group of Asians sitting down in traditional wear. | |
00022d4ab40477d67e72 | A woman is harvesting crops. | |
0002325906c84da26877 | Two men are riding scooters on the road. | |
000272014b15321959b6 | The structure employs the arts and architecture of different eras. | |
00027613c9565bdbfb46 | A seating girl tosses a soccer ball. | |
00027623b3603c597a4c | He hit the table hard a couple of times. | |
00029424eba652bbdb88 | There is a trailer. | |
0002991b12c4bfcb7ea7 | No training was given. | |
00029cf2d68d61ae73c4 | I had a good idea of what Ben Franklin wouldn't do in this situation. | |
0002a774777775001b93 | A person is wearing a uniform. | |
0002a949271f4cab2cbc | Someone is holding a basketball. | |
0002f6d079a41d2b52bc | A man is walking on a tight rope. | |
0002f8ca2ac8666d21b1 | The men are on top of the structure. | |
0003014ec44856d62ca9 | A boy is running a race. | |
00031afe69abf8016b99 | Two children are sitting in front of a bookcase, while one girl reads a book. | |
00033299f32448473ba8 | A guy is preparing food at a market. | |
000334f9481a7b6b691f | A guy carries another guy. | |
00033bbe67b1220c51ee | The man is only partially-clothed. | |
0003695758a64d7a0973 | The woman is trying to stop the oncoming traffic | |
00039002ec55727f5980 | Boy is swimming along the coast | |
0003982803255a111304 | The woman's clothes are not all of the same color. | |
0003c5db76f5b0ac7a4c | Ca'daan was happy when he heard what the man said. | |
0003e1feed8f979b9386 | Accountability from company owners gets worse performance from managers. | |
0003e61ee1881b335213 | One woman speaking into a microphone while a second woman writes beside her. | |
0004207057963f576092 | A dog jumps into a swimming pool. | |
00042afcf412417106f7 | Price jewellery and coins were discovered on the island. | |
00043e2bd138b206d8a7 | A brown dog chases a blond one in the grass. | |
000456d23a47839c6312 | Edo was renamed to Tokyo and was then considered the capital city. | |
00046b512c252b6dba6c | The dog cheers up my wife's mother. | |
00049ca88187b6151a10 | She doesn't bother me, I am used to seeing women in roles like that. | |
0004e0cf17f7dd3d348f | There are children doing sports. | |
0004e26ccf4dc4d79a7d | An animal is standing in front of a car. | |
0004ee9d4f36a55053cf | Albemarle is where we were residing. | |
00050e59d9b276d1bdee | Nobody offers free legal services in Butler County. | |
000510890e3502e66ae7 | That isn't right | |
00051384fc96dc58ca12 | Seekers were sometimes tested several times before they were accepted. | |
0005218c6d98a4ab650c | We are not the same. | |
00054192d49abeecd238 | I've got a little more time now, but I'm still pretty busy. | |
00055b59a09ee5a48c3b | The woman is taking off socks. | |
00057e245119c118d164 | .I wish I had money to spend. | |
0005fe1f0e076058d59d | The people are praying out doors. | |
0006012dd6f3aa885616 | More than likely, my satisfaction with be content. | |
000642f4108a5a7df7d4 | He looked them in the eye. | |
00067e87e1db7cda99f4 | He did not really understand the issues. | |
00068280e148fdff5698 | Paula Van Gelder's personal portraits reminded me of the squirrel a friend reported recently. | |
00068abe7cc8585f2722 | I prefer having a month of very cold weather and temperant weather for the rest of the year, than only a small portion being warm weather. | |
0006904effa5d9c3fd59 | Someone is holding cards. | |
00069171f93096b75738 | The shop is closed for the night. | |
00069ff2c250f79a16fc | The man is watching the dog go through an obstacle course. | |
0006a378b7d86b91f4c9 | Lee was working as supreme court judge. | |
0006a773b8c93850e753 | A wet black dog is running away from another black dog. | |
0006b6a5daa3d9676314 | The man is on a hunger strike and sitting in a meadow meditating. | |
0006f44f5e66fd90d5c2 | The man is standing at a table. | |
000700c2a74aff0e0651 | Auditors should not consider the risk of noncompliance when planning tests of compliance. | |
000738cfd9e65bdf4d9e | Why is nailing her to the cross? | |
0007538437e723989c41 | Boys, dressed in uniforms, stand in the rain. | |
000761a5cc28afe6395e | There were no mosquitos or other bugs for a 3 mile radius. | |
000763b3476a6944dd47 | A crowd of people is in front of a woman. | |
000775b67446280647b0 | On the grass near the water, a person in a yellow hat walks carrying fishing gear. | |
00078e042c3b9c0b013e | The little kid is playing in the mud. | |
00079a53a886bfb351ff | A large crowd is wating a race | |
0007e1395c265110fb09 | children dig via dirt | |
0007ea17518b051df96e | A man is looking at documents inside a room with another man watching him. | |
0007ef9e5034363866bd | A squatting woman wearing a hat touching the ground. | |
00080b6926d13ca0be42 | The bike has a single rider. | |
00081a2b5dbe9ff84126 | The man and child are not wet. | |
00083b7f754946eebc51 | A vendor is selling hot dogs in the stadium. | |
00084731f33d08f57709 | The lobby of the Salmon Corp was crowded. | |
0008605c17315e12c33c | The man and his wife that live down the street have never had any children. | |
00089fff65504ab6d7ef | There are people watching the performance. | |
0008a2163e0b214b81a6 | The procedure is based on the Federal Government's projections. | |
0008a6cbf06531cac2d7 | i didn't find it easy to get a high score on the verbal part of the test | |
0008ac4c194a5da0771b | One out of every two people will be drug tested starting tomorrow. | |
0008d370a7e8d5a351b2 | There's a woman waiting in line to buy something at a shop. | |
0008dc4a79a5b9340c3e | A man and a woman are in a diner. | |
0008ed70fcea6d5bf767 | A kid sitting on a swing set. | |
0008f374e2c3844a7e5f | professional motorcycle racer turning a corner | |
000920d676405296b464 | Default is what happens when someone meets their obligations under contract. | |
00093303f5b5a2d129cb | The girls are standing in water. | |
00093bc4c8ddce7fadeb | I was monitored round the clock while pregnant. | |
000967ce67651fd466fc | Were we going to watch it? | |
00096cecd0cefa1d1834 | He can't seem to break his mentor's record. | |
000974c165fc52eee1b9 | The womn wore colorful Saris. | |
000a10f200657959bf08 | The humor was not racist. |
End of preview. Expand in Data Studio
AllNLI — Training, unified schema
A normalised copy of the dataset behind the mteb task AllNLI, a retrieval training set built from sentence-transformers/all-nli. 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/all-nli @ d482672c8e74 (the revision pinned in mteb) |
| Domain · languages | NLI · eng |
| Queries / documents / qrels (all splits) | 294,930 / 620,710 / 345,225 |
| Qrels per query | min 1 · mean 1.098 · max 3 |
| Score values | 1 ×6,821 |
| Layout | queries · corpus · qrels · hard-negatives · teacher-scores, split train; queries/qrels/hard-negatives also carry dev, test — one shared corpus |
| Splits | corpus: train · hard-negatives: train, dev, test · qrels: train, dev, test · queries: train, dev, test · teacher-scores: train, dev, test |
| Hard negatives | sources: dataset · 324,881 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 (849,330 collapsed) |
| Pair recovery | 671,325 of 671,325 source pairs reconstructed from queries × qrels × corpus with byte-equal text |
| Direction | symmetric source: the first text is the query, the second the document — a convention, both texts are in the corpus |
| License | cc-by-sa-4.0 |
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
from datasets import load_dataset
queries = load_dataset("Hyukkyu/train-all-nli", "queries", split="train")
corpus = load_dataset("Hyukkyu/train-all-nli", "corpus", split="train")
qrels = load_dataset("Hyukkyu/train-all-nli", "qrels", split="train")
License and attribution
The data is redistributed under the source's terms — cc-by-sa-4.0. 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/all-nli).
This repository is an independent repackaging and is not affiliated with the RTEB or MTEB maintainers.
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