A fine-tuned GliNER model reaches 68.98% exact F1 and 75.64% fuzzy F1 on a new Italian historical NER benchmark, outperforming zero-shot LLaMa3.1-8B and zero-shot GliNER.
Santini, ZibaldonED: Silver annotations for Entity Disambiguation from Digitalzibaldone, 2024
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's Zibaldone
A fine-tuned GliNER model reaches 68.98% exact F1 and 75.64% fuzzy F1 on a new Italian historical NER benchmark, outperforming zero-shot LLaMa3.1-8B and zero-shot GliNER.