Accurate disaster entity recognition based on contextual embeddings in self-attentive BiLSTM-CRF.
Automated extraction of disaster-related named entities is crucial for gathering pertinent information during natural or human-made crises. Timely and reliable data is vital for effective disaster management, benefiting humanitarian response authorities, law enforcement agencies, and other concerned...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0318262 |
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