In the context of evolving European and national policies for research infrastructure governance, this paper presents the contribution of a national consortium for language resources and technology to the construction of a national infrastructure for FAIR and interoperable language and cultural data within a broader Humanities and Heritage Open Science initiative. As the national node of a European research infrastructure for language resources, the consortium contributes to translating FAIR and Open Science principles into practice by integrating technical, methodological, and training dimensions. Its activities combine several coordinated components: FAIRification workflows and ontology-based metadata mediation to enhance semantic interoperability across infrastructures; the refactoring and exposure of services through a federated API gateway; and the implementation of a Linguistic Linked Open Data (LLOD) pilot for the validation, transformation, and publication of interoperable RDF datasets. A national training ecosystem — comprising a training platform and a FAIR learning library — supports capacity building and the creation of FAIR-by-design learning materials. Finally, a permanent research observatory monitors community practices and needs, providing evidence-based insights for the continuous improvement of services and training provision. Together, these components demonstrate a coherent strategy for implementing FAIR and Open Science at the national level, while ensuring alignment with major European and national initiatives in the SSH data ecosystem.

This paper addresses a computational philology task focused on the automatic restoration of textual gaps (i.e., lacunae) in the Herculaneum Papyri, whose Ancient Greek texts are inherently fragmentary due to damage caused by carbonization. The objective of this work is to show the preliminary results concerning the development of a web-based suggestion service for proposing plausible supplements to fill lacunae, thereby supporting the philological process of producing new critical editions within a new web-based digital scholarly editing environment. To automatically provide such suggestions, we have developed systems that generate textual supplements in Ancient Greek, employing both neural (BERT-like) and statistical (n-gram) language modeling approaches.

“Voices of the Great War” is the first large corpus of Italian historical texts dating back to the period of First World War. This corpus differs from other existing resources in several respects. First, from the linguistic point of view it gives account of the wide range of varieties in which Italian was articulated in that period, namely from a diastratic (educated vs. uneducated writers), diaphasic (low/informal vs. high/formal registers) and diatopic (regional varieties, dialects) points of view. From the historical perspective, through a collection of texts belonging to different genres it represents different views on the war and the various styles of narrating war events and experiences. The final corpus is balanced along various dimensions, corresponding to the textual genre, the language variety used, the author type and the typology of conveyed contents. The corpus is fully annotated with lemmas, part-of-speech, terminology, and named entities. Significant corpus samples representative of the different “voices” have also been enriched with meta-linguistic and syntactic information. The layer of syntactic annotation forms the first nucleus of an Italian historical treebank complying with the Universal Dependencies standard. The paper illustrates the final resource, the methodology and tools used to build it, and the Web Interface for navigating it.

The Ancient Greek WordNet (AGWN) and the Dynamic Lexicon (DL) are multilingual resources to study the lexicon of Ancient Greek texts and their translations. Both AGWN and DL are works in progress that need accuracy improvement and manual validation. After a detailed description of the current state of each work, this paper illustrates a methodology to cross AGWN and DL data, in order to mutually score the items of each resource according to the evidence provided by the other resource. The training data is based on the corpus of the Digital Fragmenta Historicorum Graecorum (DFHG), which includes ancient Greek texts with Latin translations.

This paper describes the process of creation and review of a new lexico-semantic resource for the classical studies: AncientGreekWordNet. The candidate sets of synonyms (synsets) are extracted from Greek-English dictionaries, on the assumption that Greek words translated by the same English word or phrase have a high probability of being synonyms or at least semantically closely related. The process of validation and the web interface developed to edit and query the resource are described in detail. The lexical coverage of Ancient Greek WordNet is illustrated and the accuracy is evaluated. Finally, scenarios for exploiting the resource are discussed.