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A Semantic Search Platform for Old Church Slavonic Texts and a case study on the Nicene – Constantinopolitan Creed

Marianna Napolitano, University of Modena and Reggio Emilia; Giovanni Puccetti, Institute of Science e Technologies of Information “A. Faedo” - CNR

Abstract [en] Semantic retrieval based on Language Models embeddings is an established approach for information retrieval from large scale textual corpora, however, its application to digital humanities and specifically to ancient languages is still limited. In this work we develop a tool for the semantic retrieval of Old Church Slavonic and Church Slavonic texts and we present an investigation, carried out by experts in Slavic Philology and Slavic Orthodoxy, of the Nicene-Constantinopolitan Creed in these languages. The main contributions of the work are two: (1) We describe the creation of a reference dataset for semantic retrieval in (Old) Church Slavonic, addressing key challenges such as the limited availability of digital corpora, fragmentation of sources, and character encoding inconsistencies; (2) We develop a tool for semantic retrieval in these languages. By collecting feedbacks from the experts using the tool to study the Creed we find that it is reliable in supporting semantic analysis of the Creed and its major strengths are: (a) identifying expressions that are semantically related to the query based on context; (b) providing access to diachronic sources and enabling assessment of their impact on the translation and transmission of texts, particularly the Creed, which conveys the core principles of the Christian faith. The experts also identified some limitations, which will serve as a basis for future work and further improvement, particularly when querying texts from manuscript corpora. These issues highlight the need to: (a) enrich the dataset with manuscript sources using OCR and HTR techniques; (b) account for script variation and historical or regional orthographic differences. Our findings highlight how the tool proposed provides both a useful infrastructure for the study of (Old) Church Slavonic as well as a proof of concept for the application of semantic based information retrieval in ancient literature. The tool is available on HORTUS, the ITSERR project website: ITSERR - Prototyping Lab

Information Visualization, Data Materialization: Thinking through Space and Scale in Literary Texts with Plotspaces

Anouk Lang, University of Edinburgh

Abstract [en] Work at the intersection of data visualization, literary studies and the spatial humanities has identified the shortcomings of digital cartographic tools and applications such as GIS in addressing the complexities and ambiguities of literary space. In this article I present a visualization approach which takes an alternative angle on this problem, using as an example the representation of scalar shifts in the poems of Emily Dickinson: the plotspace, a 3D-fabricated sculptural object which can be printed in plastic or resin or milled out of materials such as metal or wood. A plotspace incorporates lines of text engraved or embossed on its inner face(s), as well as a curved shape which, extending in a three-dimensional wave-like form, plots the shifts in the size of entities referred to in the text. Plotspaces, I argue, have the capacity to prompt and provoke their viewers to go beyond the usual processes involved in close reading, by considering what is illuminated by reading a text in conjunction with a three-dimensional form which fabrication technologies make it relatively easy for non-specialists to create for themselves. In addition to these literary and hermeneutic affordances, plotspaces also raise questions about what it means to model spatiality in literary texts, and what tactility, materiality and sensory apprehension might add to the interpretive experience of reading a poem. They also speak to prevailing concerns engaging feminist visualization scholars about the conditions in which knowledge objects such as data visualizations are produced, and the shaping effects of those conditions.

ITALMUD: a Computational Terminology of the Italian Translation of the Babylonian Talmud

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Responsible AI and the Middle Ages: Detecting Historical Toxicity in Medieval Datasets

Delphine Demeles, University of Southampton

Abstract [en] The increasing reliance on open-source datasets for training large language models has revealed a critical oversight in artificial intelligence development: the presence of historical toxicity embedded within canonical literary texts. This article examines the application of contemporary toxicity detection models to the Chanson de Roland, one of medieval French foundational literary works, exposing significant challenges in identifying hate speech, violence advocacy, and discriminatory content within historical documents. Using the multilingual Detoxify model on Joseph Bédier's modern French translation, I analyze 2,605 sentences to assess how toxicity detection models trained primarily on contemporary social media content perform when evaluating medieval literature. My findings reveal a troubling pattern: While the model successfully flags some explicit threats and insults, it systematically fails to detect the text's most problematic content, including religious misrepresentation, forced conversion narratives, and anti-Black racism. These “false negatives” represent a fundamental problem for AI models being trained on historical open data, as they risk perpetuating and amplifying centuries-old discriminatory frameworks while appearing objective. This research contributes to urgent debates about responsible AI development, arguing that without human-annotated ground truth datasets specifically designed for historical texts toxicity, current LLMs risk distorting historical understanding and diffusing undetected violent and racist discrimination at unprecedented scale. I advocate for interdisciplinary collaboration between computer scientists and humanities scholars to develop ethical frameworks for curating historical datasets that acknowledge their toxic content without either sanitizing history or amplifying historical harm.

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Articles

Test Article: Code Samples

Julia Flanders, Northeastern University

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DHQ Test Article: Beastiary

Julia Flanders, Northeastern University; John A. Walsh, Indiana University

Test Article Demonstrating RevisionNote: Revised

DHQ, None

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[fr] Article Expérimentale: En Français
[en] Test Article: French-Language Article with Stub Translation
[es] Artículo de prueba: artículo en francés con traducción de esbozo

DHQ, None

Abstract [fr][en][es]

[en] Test Article: Foreign Language with Full Translation
[fr] Bienvenue à Digital Humanities Quarterly

Julia Flanders, Brown University; Wendell Piez, Mulberry Technologies, Inc.; Melissa Terras, University College London

Abstract [en][fr]

Media Encoding Samples

Julia Flanders, Northeastern University

Abstract [en]

Math Encoding Sample

Julia Flanders, Foo

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Sample Field Report

Julia Flanders, Foo

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[it] Il Titolo dell'Articolo

Benjamin Grey, Digital Humanities Quarterly; Josiah Carberry, Psychoceramics Department, Brown University; Jean-Baptiste Botul, Association of the Friends of Jean-Baptiste Botul

Abstract [en]

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