WebNLG-IT: Construction of an aligned RDF-Italian corpus through Machine Translation techniques
Year: 2025
Type: conference-paper
Abstract: The main goal of this work is the creation of the Italian version of the WebNLG corpus through the application of Neural Machine Translation (NMT) and post-editing with hand-written rules.To achieve this goal, in a first step, several existing NMT models were analyzed and compared in order to identify the system with the highest performance on the original corpus.In a second step, after using the best NMT system, we semi-automatically designed and applied a number of rules to refine and improve the quality of the produced resource, creating a new corpus named WebNLG-IT.We used this resource for fine-tuning several LLMs for RDFto-text tasks.In this way, comparing the performance of LLM-based generators on both Italian and English, we have (1) evaluated the quality of WebNLG-IT with respect to the original English version, (2) released the first fine-tuned LLM-based system for generating Italian from semantic web triples and (3) introduced an Italian version of a modular generation pipeline for RDF-to-text.
Institution: University of Turin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4412888368