Datasets:

TomMoeras
/

wmt26-lt3-sorbian-data

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+---
+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/`.
+- Model weights: https://huggingface.co/TomMoeras/wmt26-lt3-sorbian
+- Code / pipeline: https://github.com/TomMoeras/wmt26-lt3-sorbian
+- Fetchers: `data/fetch_pools.py` (pool) and `data/fetch_training_sets.py` (training) in the
+  code repo pull this dataset and verify every file's sha256 against the frozen manifests
+  (`data/pool_hashes.json`, `data/regeneration_recipe.json`).
+## `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.

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