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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.01938 |
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| _version_ | 1866916773186502656 |
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| author | Cardillo, Franco Alberto Debole, Franca Frontini, Francesca Aelami, Mitra Chahinian, Nanée Conrad, Serge |
| author_facet | Cardillo, Franco Alberto Debole, Franca Frontini, Francesca Aelami, Mitra Chahinian, Nanée Conrad, Serge |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_01938 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Novel Benchmark for NER in the Wastewater and Stormwater Domain Cardillo, Franco Alberto Debole, Franca Frontini, Francesca Aelami, Mitra Chahinian, Nanée Conrad, Serge Computation and Language 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. |
| title | Novel Benchmark for NER in the Wastewater and Stormwater Domain |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2506.01938 |