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Enregistrement W7080119719 · doi:10.5281/zenodo.17062144

TranscriboQuest2025 Medieval Vernacular Religious Texts

2025· dataset· en· W7080119719 sur OpenAlexaffabout

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2025
Typedataset
Langueen
DomaineComputer Science
ThématiqueGeochemistry and Geologic Mapping
Établissements canadiensUniversité de Montréal
Organismes subventionnairesAgence Nationale de la RechercheEuropean Commission
Mots-clésVernacularMiddle AgesHistoriographyPoetryGermanCompendium

Résumé

récupéré en direct d'OpenAlex

Team Medieval Vernacular Religious Texts **Description** This dataset was created by a collaborative working group with the aim of transcribing medieval vernacular religious texts across a range of European languages. To reflect the linguistic expertise of the group members, the project included Old and Middle French, Old and Middle Irish, Old Castilian, Old Swedish, and Early New High German (Bavarian). Religious texts were chosen as a common thread because of their wide diffusion in the European vernacular tradition, their high survival rate in manuscripts, and their relevance for the study of medieval cultural and textual practices. The dataset is based on manuscripts preserved in France, Spain, Sweden, Germany, and Ireland, dating from the 11th to the 15th centuries, with a particular concentration in the 15th century. All manuscripts belong to the category of medium to highly decorated literary manuscripts. They are written in clearly identifiable scripts, predominantly in one or two columns; two manuscripts also include marginal texts. **Text** The transcribed texts represent a wide spectrum of medieval vernacular religious writing across Europe. They include hagiographic works such as the *Legend om S. Barbara* in Old Swedish and the *Legenda aurea* in Old Castilian, devotional poetry like the *Amra Colum Cille* in Old/Middle Irish, as well as historiographical and moralizing texts such as Simon de Hesdin’s and Nicolas de Gonesse’s French translation of Valerius Maximus (*Les Faits et Dits Mémorables*). Other contributions comprise Marian devotional literature (*La conception Nostre Dame*), vernacular adaptations of Latin translations (*Décadas de Tito Livio* in Old Castilian), and the widespread compendium *Der Heiligen Leben* in Early New High German (Bavarian) again based on the Legenda Aurea. **Script** The manuscripts reflect the diversity of medieval book hands used in different European regions between the 11th and 15th centuries. They include early Insular Carolingian minuscule, as well as various Gothic books and cursive hands characteristic of high and late medieval manuscript culture. Our dataset is composed of following texts : | Manuscript | Date | Language | Text | Scripta | Number of transcribed lines | Name of the transcriptor | | :---- | :---- | :---- | :---- | :---- | :---- | :---- | | Paris, BnF, fr. 282 | 1401 | Middle French | Les Faits et Dits Mémorables de Valère le Grant, by Simon de Hesdin and Nicolas de Gonesse | Gothic cursiva | 192 | Roxane Bougrelle | | Paris, BnF fr. 818 | 1251-1300 | Old French | La conception Nostre Dame | Gothic | 143 | Catherine Dehaut | | Dublin, RIA 23 E 25, pp. 5-8 | 11-12th c (MS). 8/9th c (Text) | Old/Middle Irish and Latin | Amra Colum Cille | Insular Carolingian miniscule | 19 | Ciaran McDonough | | Stockholm, KB A 110, ff. [250r] | 1385-1400 | Old Swedish | Legend om S. Barbara, from Codex Oxenstiernianus (Järtteckensboken) | Cursiva gothica recentior | 110 | Pontus Henningsson | | Escorial, ms. h-I-14 | 13-14th c. | Old Castillan | Legenda aurea | Gothic cursiva | 141 | María Florencia Vieira | | Munich, University Library, 2° Cod. ms. 314 | 15th c. | Bavarian, Early Modern | Der Heiligen Leben (Sommerteil) | Bastarda | 287 | Barbara Denicolò | | BNE ms. 12732 | 1433 | Old Castilian | Décadas de Tito-Livio (Pero López de Ayala from Bersuire’s translation) | Gothic Cursiva | 141 | Irene Salvo García | The following metrics displayed below our corpus consisting of the manuscripts listed in the table above: in terms of its total number of documents (18); number of regions (74); total number of lines (1279); total number of words (11365); total number of characters (59696): **Dataset structure** The data folder contains each manuscript and its transcriptions. For each manuscript, the transcription is provided in an ALTO XML, along with a METS XML file, along with images of the manuscript pages that were transcribed. These are provided in one folder per manuscript as a subfolder to the data folder. **Guidelines** We followed the guidelines of the project CatMus (1.6) : Pinche, A., Clérice, T., Vlachou-Efstathiou, M., Chagué, A., Camps, J.-B., Gille Levenson, M., Brisville-Fertin, O., Boschetti, F., Fischer, F., Gervers, M., Boutreux, A., Manton, A., Gabay, S., & Ferrante, G. (2025). CATMuS Medieval (1.6.0). Zenodo. [https://doi.org/10.5281/zenodo.15030337](https://doi.org/10.5281/zenodo.15030337) And used the SegmOnto controlled vocabulary : Simon Gabay, Ariane Pinche, Kelly Christensen, Jean-Baptiste Camps, Nicola Carboni, *SegmOnto, A Controlled Vocabulary to Describe the Layout of Pages*, version 0.9, Genève/Lyon/Paris, 2023, [https://segmonto.github.io/](https://segmonto.github.io/) For our collective project, we decided to follow some common guidelines : **Segmentation guidelines** **MainZone** : see SegmOnto. MainZone contains principle text, as a single block, without any paratext. If there are many columns, we made different blocks. Interlinear glosses are part of the MainZone. **NumberingZone** : see SegmOnto. Contains page numbers or folio numbers. **GraphicZone** : images or decorations. **MarginTextZone** : marginal glosses or additions. **DropCapitalZone** : see SegmOnto. Any type of capital letters, without any subtype. Do not transcribe it. **RunningTitleZone** : see SegmOnto. Zone containing a running title. **DefaultLine / default (Kraken Result)** : standard textline. **HeadingLine** : Any heading, without consideration for the level. **InterlinearLine** : Any line between standard baseline. Verse initials (appearing at the start of each line of a versified text, similar in size to the remaining text of the verse) should be included in the line of the corresponding verse. They should thus be segmented in the MainZone as normal text. Some initial letters (not illuminated), which hang slightly below the line are not included in the mask, meaning that they have to be later added to the transcription. **Transcription guidelines** We also followed the CATMus guidelines when transcribing our documents. Given the diversity of our corpus, we chose a graphemic transcription system. Allographic variants (‘u/v’ and ‘i’/’j’) were normalised. When it comes to ‘z’/’s’, every allograph of ‘s’ was transcribed by ‘s’, and we made a difference between ‘s’ and ‘z’. We didn’t separate agglutinated words and verse initials were to be kept separated (using a space) from the rest of the word. When it comes to the choice of signs, we used four main signs: “.” for single dots, “:” for more than single dots, “/” for diastoles and signs that look like virgulas and “¶” for section markers. We didn’t normalize capital letters. We also transcribed hyphenations and diastoles. Also, if a character does not exist in MUFI but carries linguistic importance and is a common occurring character in a manuscript, a new character can be created by combining MUFI characters and symbols. Abbreviations were not developed and we transcribed them adhering to MUFI. In other words, we transcribe what we see, so that the dataset works for every vernacular language of our corpus. Every character is described in the CatMus guidelines: [https://catmus-guidelines.github.io/html/guidelines/en/character\_table.html](https://catmus-guidelines.github.io/html/guidelines/en/character_table.html) For the transcription of the manuscript in Old Swedish, specifically, a new combination of characters, “a̶ ” (small antiphon), was created since it is a common occurrence in Old Swedish manuscripts and carries linguistic importance. The character “a̶ ” has similar pronunciation as “ä” and “æ”, but since these letters appear in other languages with other pronunciation/meaning and look different than the small antiphon, a new character was created. A large antiphon already exists in MUFI, [https://mufi.info/q.php?p=mufi/chars/unichar/59610](https://mufi.info/q.php?p=mufi/chars/unichar/59610), but the small one does not. In the future, hopefully the small antihpon, “a̶ “, will be added to MUFI. **Creators of the dataset** Ciaran McDonough, Aarhus University 0000-0002-5198-9205 Pontus Henningsson, Linneaus University, 0009-0002-8956-7312 Barbara Denicolò, Paris Lodron University of Salzburg, 0000-0001-7155-9790 Roxane Bougrelle, Université Lumière Lyon 2, 0009-0002-6343-2305 Catherine Dehaut, Université de Montréal, 0009-0000-5161-7906 María Florencia Vieira, ENS de Lyon, 0009-0001-8222-1178 Irene Salvo García, Universidad Autónoma de Madrid 0000-0003-0155-1886

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,035
Score d'incertitude au seuil0,118

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,005
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0070,006
Études des sciences et des technologies0,0020,001
Communication savante0,0030,001
Science ouverte0,0010,002
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0350,059

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,018
Tête enseignante GPT0,237
Écart entre enseignants0,219 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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