Document - Novel benchmark for NER in the wastewater and stormwater domain

2025

Conference article Open Access

Novel benchmark for NER in the wastewater and stormwater domain

Cardillo F. A., Debole F., Frontini F., Aelami M., Chahinian N., Conrad S.

Wastewater networks Computation and Language (cs.CL) LLMs for NER Named Entity Recognition Multilingual NLP FOS: Computer and information sciences [SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing Annotation projection Urban hydrology Domain-specific corpus Computer Science - Computation and Language

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.

Source: COLLOQUIUM IN INFORMATION SCIENCE AND TECHNOLOGY, pp. 226-231. Marrakech, Morocco, 2025

Publisher: Institute of Electrical and Electronics Engineers

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@inproceedings{oai:iris.cnr.it:20.500.14243/562981,
	title = {Novel benchmark for NER in the wastewater and stormwater domain},
	author = {Cardillo F.  A. and Debole F. and Frontini F. and Aelami M. and Chahinian N. and Conrad S.},
	publisher = {Institute of Electrical and Electronics Engineers},
	doi = {10.1109/cist65886.2025.11224095 and 10.48550/arxiv.2506.01938},
	booktitle = {COLLOQUIUM IN INFORMATION SCIENCE AND TECHNOLOGY, pp. 226-231. Marrakech, Morocco, 2025},
	year = {2025}
}