2026-06-06T01:17:13Zhttps://iris.cnr.it/oai/requestoai:iris.cnr.it:20.500.14243/5629812026-01-16T01:15:20Zcom_20.500.14243_46com_20.500.14243_21col_20.500.14243_47ou_ou294ou_ou239
Novel benchmark for NER in the wastewater and stormwater domain
Cardillo F. A.
Debole F.
Frontini F.
Aelami M.
Chahinian N.
Conrad S.
Cardillo, F. A.
Debole, F.
Frontini, F.
Aelami, M.
Chahinian, N.
Conrad, S.
Annotation projection
Domain-specific corpus
LLMs for NER
Multilingual NLP
Named Entity Recognition
Efficient wastewater and stormwater management is mandatory for sustainable cities. Extracting structured knowledge from reports and regulations is challenging due to domain-specific terminology and multilingual contexts. This work focuses on domain-specific Named Entity Recognition (NER) as a first step towards effective relation and information extraction to support decision making. A multilingual benchmark is crucial for evaluating these methods. This study develops a French-Italian domain-specific text corpus for wastewater management. It evaluates state-of-the-art NER methods, including LLM-based approaches, to provide a reliable baseline for future strategies and explores automated annotation projection in view of an extension of the corpus to new languages.
2025
info:eu-repo/semantics/conferenceObject
https://hdl.handle.net/20.500.14243/562981
10.1109/cist65886.2025.11224095
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-105024952471
info:eu-repo/semantics/altIdentifier/isbn/979-8-3315-4384-6
https://ieeexplore.ieee.org/document/11224095
eng
ispartofbook:Cist 2025 proceedings
Cist 2025 - 8th IEEE International Congress on Information Science and Technology
firstpage:226
lastpage:231
numberofpages:6
serie:COLLOQUIUM IN INFORMATION SCIENCE AND TECHNOLOGY
info:eu-repo/semantics/restrictedAccess
ELETTRONICO
Institute of Electrical and Electronics Engineers
country:USA
license:NON PUBBLICO - Accesso privato/ristretto
license uri:iris.PRI01