| Title: |
Leveraging LLMs for Event Extraction in Italian Documents: a Roadmap for Future Research |
| Authors: |
Rollo F.; Bonisoli G.; Po L. |
| Contributors: |
Rollo, F.; Bonisoli, G.; Po, L. |
| Publisher Information: |
CEUR-WS |
| Publication Year: |
2024 |
| Collection: |
Archivio della ricerca dell'Università di Modena e Reggio Emilia (Unimore: IRIS) |
| Subject Terms: |
event extraction; Italian language; Large Language Model |
| Description: |
Event extraction is a task of significant interest in the field of Natural Language Processing (NLP) and plays a vital role in various applications, such as information retrieval and document summarization. Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. In this paper, we present a roadmap for the application of LLMs for event extraction from Italian documents, aiming to address the gap in research and resources for event extraction in non-English languages. We first discuss the challenges of event extraction and the current state-of-the-art approaches based on LLMs. Next, we present potential Italian datasets suitable for adapting linguistic models to the domain of event extraction. Furthermore, we outline future research directions and potential areas for improvement in this evolving field. |
| Document Type: |
conference object |
| Language: |
English |
| Relation: |
ispartofbook:CEUR Workshop Proceedings; 2024 Ital-IA Intelligenza Artificiale - Thematic Workshops, Ital-IA 2024; volume:3762; firstpage:18; lastpage:23; serie:CEUR WORKSHOP PROCEEDINGS; https://hdl.handle.net/11380/1360686 |
| Availability: |
https://hdl.handle.net/11380/1360686 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.BDDC3799 |
| Database: |
BASE |