This paper presents a detailed analysis of the annotation process used in the ITALERT (Italian Emergency Response Text) corpus, specifically designed to evaluate the performance of neural machine translation (NMT) systems and large language models (LLMs) in translating high-stakes messages from Italian to English.

Towards a reliable annotation framework for crisis MT evaluation: Addressing error taxonomies and annotator agreement

Maria Carmen Staiano;Johanna Monti;Chiusaroli Francesca
2025-01-01

Abstract

This paper presents a detailed analysis of the annotation process used in the ITALERT (Italian Emergency Response Text) corpus, specifically designed to evaluate the performance of neural machine translation (NMT) systems and large language models (LLMs) in translating high-stakes messages from Italian to English.
2025
Inglese
AA.VV
Corpus Linguistics 2025
contributo
The thirteen international corpus linguistics conference
212
212
1
https://u-pad.unimc.it/bitstream/11393/360131/1/CL2025 Book Of Abstracts_24th June.pdf
30 June - 3rd July 2025
Birmingham
Internazionale
ITALERT corpis, neural machine translation
4
Staiano, Maria Carmen; Han, Lifeng; Monti, Johanna; Chiusaroli, Francesca
info:eu-repo/semantics/conferenceObject
open
274
4 Contributo in Atti di Convegno (Proceeding)::4.2 Abstract in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11574/248746
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