Leveraging LLMs to Build a Semi-synthetic Dataset for Legal Information Retrieval: A Case Study on the Italian Civil Code and GPT4-O - ACL Anthology

This is an internal, incomplete preview of a proposed change to the ACL Anthology. For efficiency reasons, we don't generate MODS or Endnote formats, and the preview may be incomplete in other ways, or contain mistakes. Do not treat this content as an official publication.

Leveraging LLMs to Build a Semi-synthetic Dataset for Legal Information Retrieval: A Case Study on the Italian Civil Code and GPT4-O

Mattia Proietti, Lucia C. Passaro, Alessandro Lenci

Anthology ID:: 2025.clicit-1.87
Volume:: Proceedings of the Eleventh Italian Conference on Computational Linguistics (CLiC-it 2025)
Month:: September
Year:: 2025
Address:: Cagliari, Italy
Editors:: Cristina Bosco, Elisabetta Jezek, Marco Polignano, Manuela Sanguinetti
Venue:: CLiC-it
SIG:
Publisher:: CEUR Workshop Proceedings
Note:
Pages:: 933–941
Language:
URL:: https://preview.aclanthology.org/info-author-pages/2025.clicit-1.87/
DOI:
Bibkey:
Cite (ACL):: Mattia Proietti, Lucia C. Passaro, and Alessandro Lenci. 2025. Leveraging LLMs to Build a Semi-synthetic Dataset for Legal Information Retrieval: A Case Study on the Italian Civil Code and GPT4-O. In Proceedings of the Eleventh Italian Conference on Computational Linguistics (CLiC-it 2025), pages 933–941, Cagliari, Italy. CEUR Workshop Proceedings.
Cite (Informal):: Leveraging LLMs to Build a Semi-synthetic Dataset for Legal Information Retrieval: A Case Study on the Italian Civil Code and GPT4-O (Proietti et al., CLiC-it 2025)
Copy Citation:
PDF:: https://preview.aclanthology.org/info-author-pages/2025.clicit-1.87.pdf

PDF Cite Search Fix data