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Datasets:
TomMoeras
/
wmt26-lt3-sorbian-data

Tasks:
Translation
Text Generation
Modalities:
Text
Formats:
json
Languages:
Upper Sorbian
Lower Sorbian
German
Size:
1M - 10M
Tags:
wmt26
sorbian
upper-sorbian
lower-sorbian
low-resource
reproduction
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files
xet
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wmt26-lt3-sorbian-data / README.md
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metadata 
license: other
language:
  - hsb
  - dsb
  - de
  - en
task_categories:
  - translation
  - text-generation
pretty_name: LT3 WMT26 Sorbian reproduction datasets
tags:
  - wmt26
  - sorbian
  - upper-sorbian
  - lower-sorbian
  - low-resource
  - reproduction

LT3 at WMT26 (Sorbian): reproduction datasets

Companion data repo for the LT3 (Ghent University) WMT26 Sorbian system-description paper. It carries the datasets needed to reproduce the submitted systems that cannot be fetched automatically from an online source. Auto-fetchable inputs are deliberately excluded: dictionaries, the organizer train/dev/test distribution, and raw public corpora already pinned in the companion repo's data/MANIFESTS/.

pool/: inference-time MT exemplar retrieval pool

The MT translation-memory pool used for fuzzy exemplar retrieval, in the per-direction <src>_<tgt>.src / .tgt layout the inference stack expects. Consumed at inference time by every FullStack system for fuzzy MT exemplar retrieval (k=3). Test-deduplicated: residual test-source material is 0 in all six directions; the twelve files' sha256 match pool_hashes.json exactly.

training/: synthetic / derived training sets

One subdirectory per regeneration_recipe.json entry (sha256-matched to the recipe). Consumed during model training.

dir what seed / generator consumed by
mt_fuzzy_compfz shipped MT training rows (1,069,344, real-only, 0/1 compfz) src/data/{composition,build_training_set}.py over the real parallel corpus, top-1 fuzzy@real submitted systems (base MT)
mr_messages MR training messages (28,147) GSM8K (CC BY 4.0) + Hendrycks MATH (MIT), translated Sorbian question / English chain-of-thought all systems (MR)

Provenance and licenses

Generators are ported and documented in the code repo under training/generators/ and data/regeneration_recipe.json; seed corpora and their licenses are enumerated in data/MANIFESTS/. MR seeds are GSM8K (CC BY 4.0) and Hendrycks MATH (MIT). The MT training rows and the full (submission) pool derive from a mixture of public Sorbian-German parallel corpora (OPUS, Leipzig CC BY-NC, WMT news-crawl research-use, mtdata, and the WMT22 organizer MT parallel) plus model back-translation (the published pool above carries the real parallel portion only); they are released here for non-commercial research reproduction, inheriting the most restrictive terms of their sources (non-commercial, attribution, research-use). Redistribution beyond research reproduction is not granted.

Deliberately excluded

  • Organizer competition data (TUM-NLP distribution: train / dev / test, and any test-set derived rows). The dev_fold and v10 training mix recipe entries embed organizer dev rows in official eval formats and are therefore regenerate-only (rebuild with the code repo's build_dev_fold.py from the organizer distribution you fetch yourself).
  • GPL dictionary payloads (soblex / dsb-spell content and the BK-tree pickles derived from them; the code repo's setup.sh builds those locally from the GPL sources).
  • SC/GC/QA synthetic and the failed QA official-format synth: not archived as single files; regenerate via training/generators/synth/ per the recipe.