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Novel Benchmark for NER in the Wastewater and Stormwater Domain

2025/06/02 by Franco Alberto Cardillo, Cardillo, Franco Alberto, Franca Debole +9
Earth and Planetary Sciences · Engineering · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Fire Detection and Safety Systems #Geophysical Methods and Applications #Underwater Acoustics Research

paper · pdf · doi:10.48550/arxiv.2506.01938

openalex publication_date 2025/06/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Effective wastewater and stormwater management is essential for urban sustainability and environmental protection. Extracting structured knowledge from reports and regulations is challenging due to domainspecific 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.

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