Hyukkyu/train-quora-duplicates

QuoraDuplicates — Training, unified schema

A normalised copy of the dataset behind the mteb task QuoraDuplicates, a retrieval training set built from sentence-transformers/quora-duplicates. 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/quora-duplicates @ 41f699770310 (the revision pinned in mteb)
Domain · languages	duplicate questions · eng
Queries / documents / qrels	86,169 / 123,703 / 149,263
Qrels per query	min 1 · mean 1.732 · max 50
Score values	1 ×149,263
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	sources: dataset · 81,148 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 (229,084 collapsed)
Pair recovery	251,025 of 251,025 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	other

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-quora-duplicates", "queries", split="train")
corpus  = load_dataset("Hyukkyu/train-quora-duplicates", "corpus", split="train")
qrels   = load_dataset("Hyukkyu/train-quora-duplicates", "qrels", split="train")

License and attribution

The data is redistributed under the source's terms — other. 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/quora-duplicates). This repository is an independent repackaging and is not affiliated with the RTEB or MTEB maintainers.