Abstract
In this paper, we conduct parsing experiments on Dante Alighieri{'}s Divine Comedy, an Old Italian poem composed between 1306-1321 and organized into three Cantiche {---}Inferno, Purgatorio, and Paradiso. We perform parsing on subsets of the poem using both a Modern Italian training set and sections of the Divine Comedy itself to evaluate under which scenarios parsers achieve higher scores. We find that employing in-domain training data supports better results, leading to an increase of approximately +17{\%} in Unlabeled Attachment Score (UAS) and +25-30{\%} in Labeled Attachment Score (LAS). Subsequently, we provide brief commentary on the differences in scores achieved among subsections of Cantiche, and we conduct experimental parsing on a text from the same period and style as the Divine Comedy.
| Lingua originale | Inglese |
|---|---|
| Titolo della pubblicazione ospite | Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024 |
| Pagine | 50-56 |
| Numero di pagine | 7 |
| Stato di pubblicazione | Pubblicato - 2024 |
| Evento | Third Workshop on Language Technologies for Historical and Ancient Languages @LREC-COLING-2024 - TORINO -- ITA Durata: 25 mag 2024 → 25 mag 2024 |
Workshop
| Workshop | Third Workshop on Language Technologies for Historical and Ancient Languages @LREC-COLING-2024 |
|---|---|
| Città | TORINO -- ITA |
| Periodo | 25/5/24 → 25/5/24 |
Keywords
- Dante Alighieri
- Natural Language Processing
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