Standard Moroccan Tamazight Corrections

CHANGELOG.md

@@ -8,17 +8,6 @@ In particular:
 1. Any updates to pre-existing files shall entail a major version bump.
 2. The inclusion of a new language, without changes to other pre-existing data, shall only entail a minor version bump.
 
-## [4.0] - 2026-03-07
-- Converted the dataset to JSONL to make contributions and visual inspection of files easier.
-- Added a basic data integrity test suite based on FLORES+'s.
-- Updated `lij_Latn` after running a newly developed spellchecker revealed several typos.
-
-## [3.0] - 2025-11-07
-- Participants to the [WMT25 Shared Task](https://www2.statmt.org/wmt25/open-data.html) contributed multiple improvements. Many thanks to all the contributors! Please don't forget to cite the relevant papers listed in [bibliography.bib](bibliography.bib).
-    - Added `fra_Latn` (see [Marmonier et al, 2025](https://aclanthology.org/2025.wmt-1.80/))
-    - Added `kyr_Cyrl`  (see [Jumashev et al, 2025](https://aclanthology.org/2025.wmt-1.84/))
-    - Updated about half of `zgh_Tfng` texts (see [Oktem et al, 2025](https://aclanthology.org/2025.wmt-1.82/))
-
 ## [2.0] - 2024-11-08
 
 ### Added

README.md

@@ -6,236 +6,13 @@ language_creators:
 license: cc-by-sa-4.0
 pretty_name: OLDI-Seed
 task_categories:
-  - text-generation
+  - text2text-generation
   - translation
-language:
-  - ace
-  - ary
-  - arz
-  - bam
-  - ban
-  - ben
-  - bho
-  - bjn
-  - bug
-  - crh
-  - dik
-  - dzo
-  - eng
-  - fra
-  - fur
-  - fuv
-  - gug
-  - hne
-  - ita
-  - kas
-  - knc
-  - lij
-  - lim
-  - lmo
-  - ltg
-  - mag
-  - mni
-  - mri
-  - nqo
-  - nus
-  - pbt
-  - prs
-  - scn
-  - shn
-  - spa
-  - srd
-  - szl
-  - taq
-  - vec
-  - zgh
 configs:
   - config_name: default
     data_files:
       - split: train
-        path: seed/*.jsonl
-  - config_name: ace_Arab
-    data_files:
-      - split: train
-        path: seed/ace_Arab.jsonl
-  - config_name: ace_Latn
-    data_files:
-      - split: train
-        path: seed/ace_Latn.jsonl
-  - config_name: ary_Arab
-    data_files:
-      - split: train
-        path: seed/ary_Arab.jsonl
-  - config_name: arz_Arab
-    data_files:
-      - split: train
-        path: seed/arz_Arab.jsonl
-  - config_name: bam_Latn
-    data_files:
-      - split: train
-        path: seed/bam_Latn.jsonl
-  - config_name: ban_Latn
-    data_files:
-      - split: train
-        path: seed/ban_Latn.jsonl
-  - config_name: ben_Beng
-    data_files:
-      - split: train
-        path: seed/ben_Beng.jsonl
-  - config_name: bho_Deva
-    data_files:
-      - split: train
-        path: seed/bho_Deva.jsonl
-  - config_name: bjn_Arab
-    data_files:
-      - split: train
-        path: seed/bjn_Arab.jsonl
-  - config_name: bjn_Latn
-    data_files:
-      - split: train
-        path: seed/bjn_Latn.jsonl
-  - config_name: bug_Latn
-    data_files:
-      - split: train
-        path: seed/bug_Latn.jsonl
-  - config_name: crh_Latn
-    data_files:
-      - split: train
-        path: seed/crh_Latn.jsonl
-  - config_name: dik_Latn
-    data_files:
-      - split: train
-        path: seed/dik_Latn.jsonl
-  - config_name: dzo_Tibt
-    data_files:
-      - split: train
-        path: seed/dzo_Tibt.jsonl
-  - config_name: eng_Latn
-    data_files:
-      - split: train
-        path: seed/eng_Latn.jsonl
-  - config_name: fra_Latn
-    data_files:
-      - split: train
-        path: seed/fra_Latn.jsonl
-  - config_name: fur_Latn
-    data_files:
-      - split: train
-        path: seed/fur_Latn.jsonl
-  - config_name: fuv_Latn
-    data_files:
-      - split: train
-        path: seed/fuv_Latn.jsonl
-  - config_name: gug_Latn
-    data_files:
-      - split: train
-        path: seed/gug_Latn.jsonl
-  - config_name: hne_Deva
-    data_files:
-      - split: train
-        path: seed/hne_Deva.jsonl
-  - config_name: ita_Latn
-    data_files:
-      - split: train
-        path: seed/ita_Latn.jsonl
-  - config_name: kas_Arab
-    data_files:
-      - split: train
-        path: seed/kas_Arab.jsonl
-  - config_name: kas_Deva
-    data_files:
-      - split: train
-        path: seed/kas_Deva.jsonl
-  - config_name: knc_Arab
-    data_files:
-      - split: train
-        path: seed/knc_Arab.jsonl
-  - config_name: knc_Latn
-    data_files:
-      - split: train
-        path: seed/knc_Latn.jsonl
-  - config_name: lij_Latn
-    data_files:
-      - split: train
-        path: seed/lij_Latn.jsonl
-  - config_name: lim_Latn
-    data_files:
-      - split: train
-        path: seed/lim_Latn.jsonl
-  - config_name: lmo_Latn
-    data_files:
-      - split: train
-        path: seed/lmo_Latn.jsonl
-  - config_name: ltg_Latn
-    data_files:
-      - split: train
-        path: seed/ltg_Latn.jsonl
-  - config_name: mag_Deva
-    data_files:
-      - split: train
-        path: seed/mag_Deva.jsonl
-  - config_name: mni_Beng
-    data_files:
-      - split: train
-        path: seed/mni_Beng.jsonl
-  - config_name: mri_Latn
-    data_files:
-      - split: train
-        path: seed/mri_Latn.jsonl
-  - config_name: nqo_Nkoo
-    data_files:
-      - split: train
-        path: seed/nqo_Nkoo.jsonl
-  - config_name: nus_Latn
-    data_files:
-      - split: train
-        path: seed/nus_Latn.jsonl
-  - config_name: pbt_Arab
-    data_files:
-      - split: train
-        path: seed/pbt_Arab.jsonl
-  - config_name: prs_Arab
-    data_files:
-      - split: train
-        path: seed/prs_Arab.jsonl
-  - config_name: scn_Latn
-    data_files:
-      - split: train
-        path: seed/scn_Latn.jsonl
-  - config_name: shn_Mymr
-    data_files:
-      - split: train
-        path: seed/shn_Mymr.jsonl
-  - config_name: spa_Latn
-    data_files:
-      - split: train
-        path: seed/spa_Latn.jsonl
-  - config_name: srd_Latn
-    data_files:
-      - split: train
-        path: seed/srd_Latn.jsonl
-  - config_name: szl_Latn
-    data_files:
-      - split: train
-        path: seed/szl_Latn.jsonl
-  - config_name: taq_Latn
-    data_files:
-      - split: train
-        path: seed/taq_Latn.jsonl
-  - config_name: taq_Tfng
-    data_files:
-      - split: train
-        path: seed/taq_Tfng.jsonl
-  - config_name: vec_Latn
-    data_files:
-      - split: train
-        path: seed/vec_Latn.jsonl
-  - config_name: zgh_Tfng
-    data_files:
-      - split: train
-        path: seed/zgh_Tfng.jsonl
----
-Click to add a cell.
+        path: seed/*.parquet
 ---
 # OLDI Seed Machine Translation Datacard
 
@@ -330,31 +107,6 @@ This can be done easily using the `-s` flag on the `git commit`.
 
 Please see the [Contribution guidelines](https://oldi.org/guidelines) for further information.
 
-### How to add a pull request
-
-1. Go to https://huggingface.co/datasets/openlanguagedata/oldi_seed/discussions, press "New pull request".
-2. In the popup window, enter a branch name and press "Create branch".
-3. On your computer, do `git clone https://huggingface.co/datasets/openlanguagedata/oldi_seed`.
-4. Checkout to your newly created branch (e.g. `cd oldi_seed && git fetch origin refs/pr/4:pr/4 && git checkout pr/4`).
-5. Check that you are logged in to the HF CLI tool (`hf auth whoami`). If not, please log into it (`hf auth login` and enter your token).
-6. Modify a file (for adding new languages, see the instructions below) and add the changes to git (e.g. `git add seed/rus_Cyrl.jsonl`).
-7. Commit with an -s flag (e.g. `git commit -s -m "fix a few typos in the Russian dev set"`).
-8. Push (e.g. `git push origin pr/4:refs/pr/4`) — important to make sure to push to the same "refs" branch!
-9. Go to the pull request page and see if it reflects your changes.
-10. When your pull request is ready, press the "Publish" button in its web interface.
-
-If you find this difficult, please contact us by email `info@oldi.org` or in our [Discord group](https://discord.gg/jJmrw3E77u)!
-
-### Testing your changes
-
-After contributing new translations or modifying existing ones, you can check that the data format is OK.
-Assuming that you have the Python packages `pytest` and `dataset` installed, you can type
-```
-pytest
-```
-in your console (in the `oldi_seed` directory), and the tests will run.
-If any of them fails, please inspect the translations, following the hints in the test output.
-
 ## Changelog
 
 See [CHANGELOG.md](CHANGELOG.md) for information about the latest changes.
@@ -377,7 +129,6 @@ See [CHANGELOG.md](CHANGELOG.md) for information about the latest changes.
 | `dik` | `Latn` | `sout2832` |         Southwestern Dinka        |                                                            |
 | `dzo` | `Tibt` | `dzon1239` |              Dzongkha             |                                                            |
 | `eng` | `Latn` | `stan1293` |              English              |                                                            |
-| `fra` | `Latn` | `stan1290` |               French              |                                                            |
 | `fur` | `Latn` | `east2271` |              Friulian             |                                                            |
 | `fuv` | `Latn` | `nige1253` |         Nigerian Fulfulde         |                                                            |
 | `gug` | `Latn` | `para1311` |         Paraguayan Guaraní        |                                                            |
@@ -385,7 +136,6 @@ See [CHANGELOG.md](CHANGELOG.md) for information about the latest changes.
 | `ita` | `Latn` | `ital1282` |              Italian              |                                                            |
 | `kas` | `Arab` | `kash1277` |      Kashmiri (Arabic script)     |                                                            |
 | `kas` | `Deva` | `kash1277` |    Kashmiri (Devanagari script)   |                                                            |
-| `kir` | `Cyrl` | `kirg1245` |              Kyrgyz               |                                                            |
 | `knc` | `Arab` | `cent2050` |   Central Kanuri (Arabic script)  |                                                            |
 | `knc` | `Latn` | `cent2050` |   Central Kanuri (Latin script)   |                                                            |
 | `lij` | `Latn` | `geno1240` |         Ligurian (Genoese)        |                                                            |

bibliography.bib

@@ -81,72 +81,3 @@
     address = "Miami, USA",
     publisher = "Association for Computational Linguistics"
 }
-
-% for French
-@inproceedings{marmonier-etal-2025-french,
-    title = "A {F}rench Version of the {OLDI} Seed Corpus",
-    author = "Marmonier, Malik  and
-      Sagot, Beno{\^i}t  and
-      Bawden, Rachel",
-    editor = "Haddow, Barry  and
-      Kocmi, Tom  and
-      Koehn, Philipp  and
-      Monz, Christof",
-    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
-    month = nov,
-    year = "2025",
-    address = "Suzhou, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.wmt-1.80/",
-    pages = "1048--1060",
-    ISBN = "979-8-89176-341-8",
-    abstract = "We present the first French partition of the OLDI Seed Corpus, our submission to the WMT 2025 Open Language Data Initiative (OLDI) shared task. We detail its creation process, which involved using multiple machine translation systems and a custom-built interface for post-editing by qualified native speakers. We also highlight the unique translation challenges presented by the source data, which combines highly technical, encyclopedic terminology with the stylistic irregularities characteristic of user-generated content taken from Wikipedia. This French corpus is not an end in itself, but is intended as a crucial pivot resource to facilitate the collection of parallel corpora for the under-resourced regional languages of France."
-}
-% for Kyrgyz
-@inproceedings{jumashev-etal-2025-kyrgyz,
-    title = "The {K}yrgyz Seed Dataset Submission to the {WMT}25 Open Language Data Initiative Shared Task",
-    author = "Jumashev, Murat  and
-      Tillabaeva, Alina  and
-      Kasieva, Aida  and
-      Omurkanov, Turgunbek  and
-      Musaeva, Akylai  and
-      Emil Kyzy, Meerim  and
-      Chagataeva, Gulaiym  and
-      Washington, Jonathan",
-    editor = "Haddow, Barry  and
-      Kocmi, Tom  and
-      Koehn, Philipp  and
-      Monz, Christof",
-    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
-    month = nov,
-    year = "2025",
-    address = "Suzhou, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.wmt-1.84/",
-    pages = "1088--1102",
-    ISBN = "979-8-89176-341-8",
-    abstract = "We present a Kyrgyz language seed dataset as part of our contribution to the WMT25 Open Language Data Initiative (OLDI) shared task. This paper details the process of collecting and curating English{--}Kyrgyz translations, highlighting the main challenges encountered in translating into a morphologically rich, low-resource language. We demonstrate the quality of the dataset through fine-tuning experiments, showing consistent improvements in machine translation performance across multiple models. Comparisons with bilingual and MNMT Kyrgyz-English baselines reveal that, for some models, our dataset enables performance surpassing pretrained baselines in both English{--}Kyrgyz and Kyrgyz{--}English translation directions. These results validate the dataset{'}s utility and suggest that it can serve as a valuable resource for the Kyrgyz MT community and other related low-resource languages."
-}
-
-% for Tamazight corrections
-@inproceedings{oktem-etal-2025-correcting,
-    title = "Correcting the Tamazight Portions of {FLORES}+ and {OLDI} Seed Datasets",
-    author = "Oktem, Alp  and
-      Farhi, Mohamed Aymane  and
-      Essaidi, Brahim  and
-      Jabouja, Naceur  and
-      Boudichat, Farida",
-    editor = "Haddow, Barry  and
-      Kocmi, Tom  and
-      Koehn, Philipp  and
-      Monz, Christof",
-    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
-    month = nov,
-    year = "2025",
-    address = "Suzhou, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.wmt-1.82/",
-    pages = "1072--1080",
-    ISBN = "979-8-89176-341-8",
-    abstract = "We present the manual correction of the Tamazight portions of the FLORES+ and OLDI Seed datasets to improve the quality of open machine translation resources for the language. These widely used reference corpora contained numerous issues, including mistranslations, orthographic inconsistencies, overuse of loanwords, and non-standard transliterations. Overall, 36{\%} of FLORES+ and 40{\%} of Seed sentences were corrected by expert linguists, with average token divergence of 19{\%} and 25{\%} among changed items. Evaluation of multiple MT systems, including NLLB models and commercial LLM services, showed consistent gains in automated evaluation metrics when using the corrected data. Fine-tuning NLLB-600M on the revised Seed corpus yielded improvements of +6.05 chrF (en{\textrightarrow}zgh) and +2.32 (zgh{\textrightarrow}en), outperforming larger parameter models and LLM providers in en{\textrightarrow}zgh direction."
-}

dataset_cards/fra_Latn.md

@@ -1,58 +0,0 @@
-# Dataset card
-
-## Description
-
-French partition of the OLDI Seed Corpus, consisting of segments sourced from Wikipedia articles.
-
-## License
-
-CC BY-SA 4.0
-
-## Attribution
-
-```bibtex
-@inproceedings{marmonier-etal-2025-french,
-    title = "A {F}rench Version of the {OLDI} Seed Corpus",
-    author = "Marmonier, Malik  and
-      Sagot, Beno{\^i}t  and
-      Bawden, Rachel",
-    editor = "Haddow, Barry  and
-      Kocmi, Tom  and
-      Koehn, Philipp  and
-      Monz, Christof",
-    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
-    month = nov,
-    year = "2025",
-    address = "Suzhou, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.wmt-1.80/",
-    pages = "1048--1060",
-    ISBN = "979-8-89176-341-8",
-    abstract = "We present the first French partition of the OLDI Seed Corpus, our submission to the WMT 2025 Open Language Data Initiative (OLDI) shared task. We detail its creation process, which involved using multiple machine translation systems and a custom-built interface for post-editing by qualified native speakers. We also highlight the unique translation challenges presented by the source data, which combines highly technical, encyclopedic terminology with the stylistic irregularities characteristic of user-generated content taken from Wikipedia. This French corpus is not an end in itself, but is intended as a crucial pivot resource to facilitate the collection of parallel corpora for the under-resourced regional languages of France."
-}
-```
-See the paper "A French Version of the OLDI Seed Corpus" at https://aclanthology.org/2025.wmt-1.80. 
-
-## Language codes
-
-* ISO 639-3: fra
-* ISO 15924: Latn
-* Glottocode: stan1290
-
-## Additional language information
-
-The data follows the grammatical and lexical norms of standard French, as spoken and written in France. However, for consistency and to align with common practices in related datasets, it adopts a few specific typographical conventions:
-* Dactylographic apostrophes (') are used systematically instead of typographic apostrophes (’).
-* The use of French _guillemets_ (« ») with non-breaking spaces is not strictly enforced, a convention also followed in the French partitions of the FLORES dataset.
-
-For authoritative guidance on the French language, the following resources are recommended. For grammar and usage, the primary reference is M. Grevisse and A. Goosse, _Le Bon Usage_ (16th ed., De Boeck Supérieur, 2016). For a comprehensive reference in English, see H. N. Labeau & P. Larrivée, _The Cambridge Grammar of French_ (Cambridge University Press, 2022). For lexicographical aspects, the main monolingual references are _Le Grand Robert de la langue française_ and A. Rey (ed.), _Dictionnaire historique de la langue française_. A standard bilingual reference is the _Collins-Robert French Dictionary_. A recent and comprehensive reference work in English covering the French language in all its facets is W. Ayres-Bennett & M. McLaughlin (eds.), _The Oxford Handbook of the French Language_ (Oxford University Press, 2024). A high-quality open-source spell and grammar checker for French is available via [Grammalecte](https://grammalecte.net/).
-
-## Workflow
-
-This dataset was created using a machine translation post-editing (MTPE) approach. Starting from the original English partition of the OLDI Seed Corpus, we generated nine translation hypotheses per segment using a mix of systems: four "traditional" sequence-to-sequence Transformer MT models (OPUS-MT, NLLB-3.3B, NLLB-600M, MADLAD-400-3B) and five hypotheses from large language models (four from Llama 4 Scout using varied prompting strategies, and one from DeepSeek-R1).
-
-This diverse set of nine translation candidates for each segment was then presented to post-editors in a custom-built interface. The interface allowed post-editors to select any of the candidate translations, which would then populate a text area for further refinement. This refinement process focused on two key aspects of the target text: improving the fluency of the translations, a non-trivial task due to the many stylistic irregularities and errors found in the user-generated source segments originating from Wikipedia; and meticulously verifying and correcting, through extensive external research, the translation of technical terminology across the wide range of specialized, encyclopedic domains represented in the corpus.
-
-As a final step, all post-edited segments underwent a validation pass using the Grammalecte grammar checker interface.
-
-This post-editing and validation work was performed by two native French speakers with a C2 level in English. A native British English speaker with a C2 level in French was also consulted to clarify specific aspects of the source segments. Domain experts were occasionally consulted to solve terminological difficulties in highly technical domains.

dataset_cards/kir_Cyrl.md

@@ -1,58 +0,0 @@
-# Dataset card
-
-## Description  
-<!-- A concise description of the data associated with this card. -->  
-Open source Seed dataset in Kyrgyz (Кыргыз тили, Кыргызча)
-
-
-
-## License  
-<!-- Contributions to existing datasets must be released under the same license as the parent dataset. For completely new contributions, we encourage the use of an open license. At a minimum, data should be made available for research use. Please specify the license using an SPDX license identifier. -->  
-CC-BY-SA-4.0  
-
-## Attribution  
-<!-- Who should be credited for creating this dataset? Feel free to include citation data in BibTeX format. -->  
-```bibtex 
-@inproceedings{jumashev-etal-2025-kyrgyz,
-    title = "The {K}yrgyz Seed Dataset Submission to the {WMT}25 Open Language Data Initiative Shared Task",
-    author = "Jumashev, Murat  and
-      Tillabaeva, Alina  and
-      Kasieva, Aida  and
-      Omurkanov, Turgunbek  and
-      Musaeva, Akylai  and
-      Emil Kyzy, Meerim  and
-      Chagataeva, Gulaiym  and
-      Washington, Jonathan",
-    editor = "Haddow, Barry  and
-      Kocmi, Tom  and
-      Koehn, Philipp  and
-      Monz, Christof",
-    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
-    month = nov,
-    year = "2025",
-    address = "Suzhou, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.wmt-1.84/",
-    pages = "1088--1102",
-    ISBN = "979-8-89176-341-8",
-    abstract = "We present a Kyrgyz language seed dataset as part of our contribution to the WMT25 Open Language Data Initiative (OLDI) shared task. This paper details the process of collecting and curating English{--}Kyrgyz translations, highlighting the main challenges encountered in translating into a morphologically rich, low-resource language. We demonstrate the quality of the dataset through fine-tuning experiments, showing consistent improvements in machine translation performance across multiple models. Comparisons with bilingual and MNMT Kyrgyz-English baselines reveal that, for some models, our dataset enables performance surpassing pretrained baselines in both English{--}Kyrgyz and Kyrgyz{--}English translation directions. These results validate the dataset{'}s utility and suggest that it can serve as a valuable resource for the Kyrgyz MT community and other related low-resource languages."
-}
-```  
-See the paper "The Kyrgyz Seed Dataset Submission to the WMT25 Open Language Data Initiative Shared Task" at https://aclanthology.org/2025.wmt-1.84/.
-
-## Language codes  
-<!-- * If this language is assigned an ISO 639-3 individual language code (not a macrolanguage code), specify it here. * Please specify the script this language is written in using an ISO 15924 code. * If this language is assigned a Glottocode, please specify it here. -->  
-* ISO 639-3: kir
-* ISO 15924: Cyrl
-* Glottocode: kirg1245
-
-## Additional language information  
-We used el-sozduk.kg, which provides multiple dictionaries including Kyrgyz-English, Kyrgyz-Russian, English-Kyrgyz, and Russian-Kyrgyz. Since Kazakh and Kyrgyz are highly mutually intelligible, we also consulted sozdik.kz (a Kazakh dictionary) to assist with translations and cross-checking. In addition, we used other English-to-Turkic language dictionaries to further inform our translations. Russian was frequently used as an intermediary language, both for dictionary lookups (e.g., via multitran.com for English-Russian) and for clarifying meanings between English and Kyrgyz or other Turkic languages.
-  
-## Workflow
-Our translation team included six native Kyrgyz speakers: two experienced translators and two students from the Kyrgyz-English Language Program at Kyrgyz-Turkish Manas University. We followed the OLDI (2025) guidelines. The workflow had four stages: (1) machine translation using Aitil (https://translate.mamtil.gov.kg/), a Gemma3-based MT service fine-tuned by Ulut Soft LLC, (2) manual correction by individual translators, (3) team terminology unification, and (4) cross-validation and peer review to ensure accuracy and consistency.
-
-## Additional guidelines  
-We created a supplementary list of terms—an English-to-Kyrgyz mini-dictionary—for words and expressions that could not be found in any existing English-Kyrgyz or Russian-Kyrgyz dictionaries. This resource is available in the paper's repository: https://github.com/kyrgyz-nlp/oldi-dataset-experiments/blob/main/mini-dictionary.txt
-
-Terminology consultation and review were led by one of the co-authors, Assoc. Prof.Dr. Aida Kasieva, Department of Simultaneous Translation, Faculty of Humanities of the Kyrgyz-Turkish Manas University. Her expertise ensured the accuracy and consistency of specialized vocabulary throughout the dataset.

dataset_cards/zgh_Tfng.md

@@ -1,50 +1,15 @@
 # Dataset card
 
-## Description  
-Seed data in Standard Moroccan Tamazight with 2025 corrections.
+## Description
 
-## License  
-CC-BY-SA-4.0  
+Seed data in Standard Moroccan Tamazight
 
-## Attribution  
-```
-@inproceedings{oktem-etal-2025-correcting,
-    title = "Correcting the Tamazight Portions of {FLORES}+ and {OLDI} Seed Datasets",
-    author = "Oktem, Alp  and
-      Farhi, Mohamed Aymane  and
-      Essaidi, Brahim  and
-      Jabouja, Naceur  and
-      Boudichat, Farida",
-    editor = "Haddow, Barry  and
-      Kocmi, Tom  and
-      Koehn, Philipp  and
-      Monz, Christof",
-    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
-    month = nov,
-    year = "2025",
-    address = "Suzhou, China",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2025.wmt-1.82/",
-    pages = "1072--1080",
-    ISBN = "979-8-89176-341-8",
-    abstract = "We present the manual correction of the Tamazight portions of the FLORES+ and OLDI Seed datasets to improve the quality of open machine translation resources for the language. These widely used reference corpora contained numerous issues, including mistranslations, orthographic inconsistencies, overuse of loanwords, and non-standard transliterations. Overall, 36{\%} of FLORES+ and 40{\%} of Seed sentences were corrected by expert linguists, with average token divergence of 19{\%} and 25{\%} among changed items. Evaluation of multiple MT systems, including NLLB models and commercial LLM services, showed consistent gains in automated evaluation metrics when using the corrected data. Fine-tuning NLLB-600M on the revised Seed corpus yielded improvements of +6.05 chrF (en{\textrightarrow}zgh) and +2.32 (zgh{\textrightarrow}en), outperforming larger parameter models and LLM providers in en{\textrightarrow}zgh direction."
-}
-```
+## License
 
-Awal initiative:
+CC-BY-SA-4.0
 
-```
-@inproceedings{oktem-boudichat-2025-awal,
-  author    = {\"Oktem, Alp and Boudichat, Farida},
-  title     = {Awal -- Community-Powered Language Technology for Tamazight},
-  booktitle = {Proceedings of the Conf{\'e}rence Internationale sur les Technologies d'Information et de Communication pour l'Amazighe (TICAM)},
-  year      = {2025},
-  address   = {Rabat, Morocco},
-  publisher = {Institut Royal de la Culture Amazighe (IRCAM)}
-}
-```
+## Attribution
 
-Original dataset:
 ```bibtex
 @inproceedings{seed-23,
     title = {Small Data, Big Impact: Leveraging Minimal Data for Effective Machine Translation},
@@ -58,29 +23,18 @@ Original dataset:
 }
 ```
 
-## Language codes  
+## Language codes
+
 * ISO 639-3: zgh
 * ISO 15924: Tfng
 * Glottocode: stan1324
 
-## Additional language information  
-Standard Moroccan Tamazight as standardized by the Royal Institute of Amazigh Culture (IRCAM), using Tifinaghe-IRCAM (Neo-Tifinagh) script. Reference materials used include:
-
-* Dictionnaire Général de la Langue Amazighe (Ameur et al., 2016)
-* Arabic-Amazigh-French Landforms Dictionary (Akioud et al., 2022)  
-* Arabic-Amazigh Dictionary (Chafik, 1996)
-* Phonologie de l'Amazighe (Boukous, 2009)
-* La Nouvelle Grammaire de l'Amazighe (Boukhris et al., 2008)
-* Grammaire Générative de l'Amazighe: Morphologie et Syntaxe du Nom (El Moujahid, 2022)
-* Manuel de Conjugaison de l'Amazighe (Laabdelaoui et al., 2012)
-
-## Workflow  
+## Additional language information
 
-The original data was released as part of the NLLB-Seed dataset, where it was incorrectly labeled `tzm_Tfng`. It was relabeled as `zgh_Tfng` after community feedback and additional quality assessment. Please refer to the paper for further information.
+Reference dictionary: IRCAM’s [Dictionnaire Général de la Langue Amazighe Informatisé](https://tal.ircam.ma/dglai/lexieam.php).
 
-The 2025 update submission contains manual corrections of Standard Moroccan Tamazight (zgh) translations that addressed mistranslations, orthographic inconsistencies, overuse of loanwords, and non-standard transliterations in the original datasets. The corrected data includes 997 sentences from FLORES+ dev, 1,012 sentences from FLORES+ devtest, and 6,193 sentences from OLDI Seed, with 36% of FLORES+ and 40% of Seed sentences requiring corrections.
+## Workflow
 
-Corrections were performed by expert linguists taking English source sentences as reference. The FLORES+ dev and devtest sets were revised in full in two iterations by two linguists. The OLDI Seed dataset was divided into batches of 1,000 sentences and distributed among three professional Tamazight translators. Quality control was ensured through spot-checking of each linguist's work by another linguist through random sampling. All translators were professional translators and were compensated as part of this work.
+This data was released as part of the NLLB-Seed dataset, where it was incorrectly labeled `tzm_Tfng`. It was relabeled as `zgh_Tfng` after community feedback and additional quality assessment. Please refer to the paper for further information.
 
-## Additional guidelines  
-Corrections followed IRCAM standardization guidelines, prioritizing native Tamazight terms over loanwords when available. For loanwords that were retained, proper Tamazight morphological patterns were applied (e.g., appropriate nominal prefixes). Transliterations of foreign words and names followed standardized practices, with particular attention to accurate mapping of sounds not present in Tamazight to their closest equivalents.
+## Additional guidelines

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