Datasets:

mischeiwiller
/

mteb-de

license: cc-by-4.0
language:
  - de
task_categories:
  - text-retrieval
tags:
  - mteb
  - german
  - retrieval
  - reranking
  - benchmark
size_categories:
  - 10K<n<100K
pretty_name: MTEB-DE — German Embedding/Retrieval Benchmark
configs:
  - config_name: germandpr-corpus
    data_files:
      - split: corpus
        path: germandpr/corpus/corpus.parquet
  - config_name: germandpr-queries
    data_files:
      - split: train
        path: germandpr/queries/train.parquet
      - split: dev
        path: germandpr/queries/dev.parquet
      - split: test
        path: germandpr/queries/test.parquet
  - config_name: germandpr-qrels
    data_files:
      - split: train
        path: germandpr/qrels/train.parquet
      - split: dev
        path: germandpr/qrels/dev.parquet
      - split: test
        path: germandpr/qrels/test.parquet
  - config_name: jobs-corpus
    data_files:
      - split: corpus
        path: jobs/corpus/corpus.parquet
  - config_name: jobs-queries
    data_files:
      - split: train
        path: jobs/queries/train.parquet
      - split: dev
        path: jobs/queries/dev.parquet
      - split: test
        path: jobs/queries/test.parquet
  - config_name: jobs-qrels
    data_files:
      - split: train
        path: jobs/qrels/train.parquet
      - split: dev
        path: jobs/qrels/dev.parquet
      - split: test
        path: jobs/qrels/test.parquet
  - config_name: jobs-hard_negatives
    data_files:
      - split: train
        path: jobs/hard_negatives/train.parquet
      - split: dev
        path: jobs/hard_negatives/dev.parquet
      - split: test
        path: jobs/hard_negatives/test.parquet

MTEB-DE — German Embedding/Retrieval Benchmark

A consolidated, reproducible German retrieval benchmark. v0 ships the retrieval task type across 2 configs; reranking / STS / clustering follow. Loaded via, e.g., load_dataset("mischeiwiller/mteb-de", "germandpr-queries") (BEIR/MTEB layout: each task = <config>-corpus / -queries / -qrels [ + -hard_negatives]).

Dataset Summary

germandpr — German open-domain QA passage retrieval (deepset GermanDPR via the CC-BY-4.0 MTEB mirror), re-split train/dev/test by query id (seed 42); the corpus is shared across splits per BEIR/MTEB index semantics.
jobs — Net-new hard German retrieval: a job title must retrieve the canonical occupation/skills profile of the same posting. Derived from Project-1 official-API job data (no verbatim postings), PII-scrubbed, with mined hard negatives.

Configurations

Each retrieval task is published as separate corpus / queries / qrels configs (plus hard_negatives where mined), so the index is shared across the train/dev/test query splits — standard BEIR/MTEB retrieval semantics.

Provenance & Licensing

All configs are CC-BY-4.0. We publish derived fields only — no verbatim, ToS-restricted source text. Source dataset and pinned revision per config:

Config	Upstream source	Loaded from	Revision	License
`germandpr`	`deepset/germandpr`	`mteb/GermanDPR`	`64a4860e55`	cc-by-4.0
`jobs`	`mischeiwiller/german-job-postings`	`mischeiwiller/german-job-postings`	`d49f1e4243`	cc-by-4.0

Splits

Queries (and their qrels / hard negatives) are partitioned by query id into train / dev / test at 0.8 / 0.1 / 0.1 with a fixed seed (42). The corpus is a single shared corpus split.

Metrics

germandpr: nDCG@10 / MRR@10
jobs: nDCG@10 / MRR@10

Hard-Negative Mining

The jobs config ships mined hard negatives. Procedure: encode queries and passages with intfloat/multilingual-e5-base@d128750597 (e5 query: / passage: prefixes), rank by cosine similarity, take top-10, drop the labelled positive(s), drop candidates within 0.05 of the positive score (false-negative guard), and keep up to 5. Full write-up + spot-audit: see the project notes/hard-negative-mining.md and notes/hard-negative-audit.md.

Limitations

germandpr is from 2021 and small (~1k queries); included for continuity.
jobs passages are composed from structured ESCO fields (occupation + skills, region, seniority, KldB) because the upstream description_derived is currently unpopulated; ESCO labels are English, making jobs a cross-lingual German-title → English-profile task in v0.
Hard negatives are mined automatically and spot-audited, not exhaustively human-verified; residual false negatives are possible.

Citation

Derived from deepset/germandpr (via the MTEB mirror) and mischeiwiller/german-job-postings. A canonical Croissant descriptor is auto-served by the Hub at the dataset's /croissant endpoint; a generated copy ships as croissant.jsonld.