A F rench Version of the OLDI Seed Corpus (2025)

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.

## introduction while state-of-the-art machine translation (mt) has made significant strides, progress has largely been concentrated on a handful of high-resource languages @xcite . for many of the world's languages, development is hindered by a lack of reliable training data @xcite . techniques like backtranslation @xcite @xcite can help bridge this gap, but they typically require an initial high-quality parallel corpus to "kickstart" the process. to address this, the oldi seed corpus was created (originally as the nllb seed dataset) to provide a small but highquality, professionally translated dataset for dozens of low-resource languages @xcite . the source material consists of approximately 6,000 english sentences sampled from a curated list of core wikipedia articles, ensuring broad topic coverage @xcite . the wmt 2025 open language data initiative (oldi) shared task builds directly on this effort, inviting the research community to expand these foundational open-source datasets to more languages. our work answers this call by adding a french partition to the oldi seed corpus. while french is a high-resource language, its selection as a pivot is strategic for our ultimate goal: facilitating the creation of parallel corpora for underresourced regional languages of france (e.g., francoprovençal, occitan, picard). translators for these languages are overwhelmingly more likely to have a native command of french than of english. most importantly, many of these languages exist in a diglossic relationship with french, which serves as the dominant language for most technical and formal domains. a french source text would, therefore, greatly simplify the complex terminological work inherent in translating the encyclopedic content found in the oldi seed corpus, enabling the creation of direct calques and other word-formation strategies that are linguistically and culturally more congruent than those derived from english. with that in mind, we went to great lengths to rigorously verify the french technical terminology throughout the data creation process. by providing this carefully curated french corpus, we aim to establish a solid foundation for future translation efforts. in addition to the final french partition, we also contribute a supplementary dataset containing the full set of translation hypotheses generated by the nine different mt systems and prompting techniques used in our workflow. this resource, which pairs multiple machine-generated outputs with a final, human-post-edited reference for each source segment, may be of particular use for research on preference optimization and quality estimation in the wikipedia domain. 1 we hope that our contribution will encourage further community-driven expansions of the oldi seed corpus. ## linguistic overview french is a romance language that evolved from the vulgar latin spoken by the inhabitants of northern gaul after the roman conquest. its development was significantly shaped by the germanic invasions of the 5th century, particularly by the franks, whose linguistic habits profoundly influenced the phonology and vocabulary of the emerging gallo-romance vernacular @xcite . the earliest extant text, the strasbourg oaths, dates to 842. over the subsequent centuries, the dialect of the île-de-france region, known as francien, gradually gained prestige due to the political and cultural centrality of paris. this parisian variety formed the basis of a standardized literary and administrative language that was progressively imposed throughout the kingdom, through a process legally enforced by the ordinance of villers-cotterêts in 1539. this history of internal linguistic unification through political centralization later provided a model for its imposition as the language of administration and education throughout france's colonial empire. today, with over 321 million speakers, french is the fifth most spoken language in the world (oif, 2022). however, this numerical strength, driven almost entirely by african demography, masks a more complex reality. recent independent assessments point to a rebalancing, with french losing ground to english in several symbolic and highvalue domains. in parts of west africa, its constitutional standing has weakened, with countries like mali and burkina faso downgrading it from an "official" to a "working" language in 2023-2024. in north africa, educational policies increasingly favor english, while in major anglophone countries, like the united kingdom and the united states, learner numbers have seen long-term declines @xcite . furthermore, english overwhelmingly dominates high-prestige domains such as scientific publishing even within france's own research output @xcite . while the language's global landscape is in flux, the variety used in this corpus, standard french as spoken in france, remains the most widely recognized norm for formal written communication. ## data collection the shared task guidelines for seed data contributions permit the use of post-edited machine transla-tion (mtpe). given the high quality of modern mt systems for the english-french language pair, we adopted this workflow. a full professional translation from scratch was deemed prohibitively expensive. counterintuitively perhaps for a "seed" corpus, the source text represents a non-trivial amount of written content; at 136,656 total words, its length is comparable to that of a novel, falling between jane austen's pride and prejudice and charles dickens' a tale of two cities. we estimated that a professional translation would have required a substantial budget-around c50,000, not accounting for the added complexity of the varied and often highly technical terminology found in the source segments-that we felt would be more strategically allocated to future translation efforts into the lowresource regional languages of france. the mtpe approach therefore allowed us to produce a highly adequate french corpus while preserving resources for our long-term goals. ## discussion while we were initially tempted to follow the validation approach of cols (2024) by training separate neural mt models on our final corpus and on each set of hypotheses, we ultimately judged that for a ## related work while data-driven approaches to mt have precedents as early as the 1950s @xcite , they did not truly come into their own until the late 1980s and early 1990s with the pioneering work on statistical machine translation (smt) at ibm @xcite . this early research was heavily reliant on the availability of large parallel corpora, and the french-english language pair played a central role, largely thanks to the canadian hansard, a bilingual record of parliamentary proceedings. so influential was this corpus that it established a lasting convention in smt literature, where the letters f and e became the standard variables to denote source (f rench) and target (english) language strings in equations, regardless of the actual languages involved. our work builds on the modern legacy of these corpusbased approaches. specifically, we contribute to the oldi seed corpus @xcite , a resource designed to bootstrap translation capabilities for low-resource languages. the oldi shared task has spurred several recent efforts to expand this dataset, including the creation of spanish @xcite , italian @xcite , and bangla @xcite partitions, each contributing to this growing ecosystem of open, multiparallel data. ## conclusion in this paper, we have presented our contribution to the wmt 2025 oldi shared task: a high-quality, human-post-edited french partition of the oldi seed corpus. we have detailed our data creation methodology, which relied on a diverse array of mt systems and approaches-from traditional nmt models to various llm prompting strategies-and a custom-built interface to facilitate an efficient and robust post-editing workflow. our experimental validation, using the state-of-the-art metricx-24 qe metric, confirmed that our final, manuallyrefined corpus is of significantly higher quality than any of the individual machine-generated hypotheses. our primary motivation for this work is to provide a reliable pivot resource to enable the future development of translation capabilities for the under-resourced regional languages of france. we hope that this dataset, along with the supplementary collection of raw mt outputs, will serve as a valuable contribution to the community and a stepping stone towards this long-term goal.