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A Bolu: A Structured Dataset for the Computational Analysis of Sardinian Improvisational Poetry

Contributo in Atti di convegno
Data di Pubblicazione:
2026
Abstract:
The growing interest of Natural Language Processing (NLP) in minority languages has not yet bridged the gap in the preservation of oral linguistic heritage. In particular, extemporaneous poetry — a performative genre based on real-time improvisation, metrical-rhetorical competence — remains a largely unexplored area of computational linguistics. This methodological gap necessitates the creation of specific resources to document and analyse the structures of improvised poetry. This is the context in which A Bolu was created, the first structured corpus of extemporaneous poetry dedicated to cantada logudorese, a variant of the Sardinian language. The dataset
comprises 2,835 stanzas for a total of 141,321 tokens. The study presents the architecture of the corpus and applies a multidimensional analysis combining descriptive statistical indices and computational linguistics techniques to map the characteristics of the poetic text. The results indicate that the production of Sardinian extemporaneous poets is characterised by recurring patterns that support Parry and Lord’s theory of formulaicity.
This evidence not only provides a new key to understanding oral creativity, but also offers a significant contribution to the development of NLP tools that are more inclusive and sensitive to the specificities of less widely spoken languages.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Keywords:
Corpus of minority languages, Extemporaneous poetry, Oral-formulaic patterns
Elenco autori:
Calderaro, Silvio; Monti, Johanna
Autori di Ateneo:
MONTI JOHANNA
Link alla scheda completa:
https://unora.unior.it/handle/11574/256040
Link al Full Text:
https://unora.unior.it//retrieve/handle/11574/256040/266245/document%20(1).pdf
Titolo del libro:
Proceedings of Workshop on Dialects in NLP — A Resource Perspective (DialRes) @ LREC 2026
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https://drive.google.com/file/d/1Yg-uSmZ2FUdO91MgDXAayWE2-LyJYNW1/view
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