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A Refined Span Classification Model for Recognizing Nested Named Entity in Marine Meteorological Disaster Texts
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Orientador(es)
Resumo(s)
Named entity recognition (NER) in marine meteorological disaster texts is essential for automated information extraction and disaster management. However, disaster-chain descriptions often contain nested entities that are difficult for conventional flat NER models to represent. This paper proposes PRSpan, a position-role-aware span classification model for nested NER. PRSpan incorporates Rotary Position Embedding (RoPE)-enhanced attention for relative position-aware boundary modeling and uses Conditional Layer Normalization (CLN) to generate role-specific Head, Mid, and Tail token features. A Positional Role Pooling strategy further aggregates these features into span representations to preserve boundary cues and internal semantic coherence. To support evaluation, we construct MMD-NER, a domain-specific dataset containing 1899 sentences, 17,017 entities in 11 categories, and 2978 nested entity pairs through a four-step LLM-assisted pipeline. Experimental results show that PRSpan achieves Micro-F1 and Macro-F1 scores of 94.58% and 93.47%, outperforming the strongest baseline by 3.61 and 3.93 percentage points, respectively. Additional analyses verify the effectiveness of RoPE-enhanced attention, role-specific feature generation, and Positional Role Pooling. Cross-domain transfer and LLM prompting comparisons further demonstrate the practical value of PRSpan for nested entity extraction in low-resource Earth science domains.
Descrição
Ni, W., Wang, W., Xie, N., Liu, T., Zeng, Q., & Liu, C. (2026). A Refined Span Classification Model for Recognizing Nested Named Entity in Marine Meteorological Disaster Texts. ISPRS International Journal of Geo-Information, 15(6), Article 258. https://doi.org/10.3390/ijgi15060258
Palavras-chave
nested named entity recognition marine meteorological disasters Natural Language Processing deep learning Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 14 - Life Below Water