PREMOVE is a diachronic dataset of Ancient Greek and Latin PREverbed MOtion VErbs, providing manually curated morphological, syntactic, and semantic annotations for almost three thousand verbal occurrences. This paper presents the integration of PREMOVE into the LiLa Knowledge Base of Latin, linking its semantic annotations to WordNet (WN) and VerbNet (VN). We describe the RDF conversion using OntoLex-Lemon and FrAC, enabling explicit modelling of token-level attestations and dataset-level provenance. The resulting linked resource achieves full FAIR compliance and supports complex SPARQL queries, allowing users to explore motion semantics across lexical, textual, and semantic layers. Example SPARQL queries demonstrate how researchers can retrieve attested forms for specific WN synsets or VN classes, supporting reproducible linguistic research and cross-resource exploration of motion semantics in ancient languages.
Farina, A., Passarotti, M. C., Mambrini, F., Pellegrini, M., Litta Modignani Picozzi, E. M. G., Moretti, G., PREMOVE in LiLa: Integrating Latin Preverbed Motion Verbs with WordNet and VerbNet, in Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026), (Palma de Mallorca, 13-15 May 2026), European Language Resources Association (ELRA), Palma De Mallorca 2026: 3672-3683. [https://doi.org/10.63317/3ifm66wvmf86] [https://hdl.handle.net/10807/335426]
PREMOVE in LiLa: Integrating Latin Preverbed Motion Verbs with WordNet and VerbNet
Passarotti, Marco Carlo;Mambrini, Francesco;Pellegrini, Matteo;Litta Modignani Picozzi, Eleonora Maria Gabriella;Moretti, Giovanni
2026
Abstract
PREMOVE is a diachronic dataset of Ancient Greek and Latin PREverbed MOtion VErbs, providing manually curated morphological, syntactic, and semantic annotations for almost three thousand verbal occurrences. This paper presents the integration of PREMOVE into the LiLa Knowledge Base of Latin, linking its semantic annotations to WordNet (WN) and VerbNet (VN). We describe the RDF conversion using OntoLex-Lemon and FrAC, enabling explicit modelling of token-level attestations and dataset-level provenance. The resulting linked resource achieves full FAIR compliance and supports complex SPARQL queries, allowing users to explore motion semantics across lexical, textual, and semantic layers. Example SPARQL queries demonstrate how researchers can retrieve attested forms for specific WN synsets or VN classes, supporting reproducible linguistic research and cross-resource exploration of motion semantics in ancient languages.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



