MFEE: a multi-word lexical feature enhancement framework for Chinese geological hazard event extraction
Event Extraction (EE) is an essential and challenging task in information extraction. Most existing event extraction methods do not specifically target the Chinese geological hazards domain. This is due to the unique characteristics of the Chinese language and the lack of Chinese geological hazard d...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2023-03-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-1275.pdf |
| Summary: | Event Extraction (EE) is an essential and challenging task in information extraction. Most existing event extraction methods do not specifically target the Chinese geological hazards domain. This is due to the unique characteristics of the Chinese language and the lack of Chinese geological hazard datasets. To address these challenges, we propose a novel multi-word lexical feature enhancement framework (MFEE). It effectively implements Chinese event extraction in the geological hazard domain by introducing lexical information and the designed lexical feature weighting decision method. In addition, we construct a large-scale Chinese geological hazard dataset (CGHaz). Experimental results on this dataset and the ACE 2005 dataset demonstrate the approach’s effectiveness. The datasets can be found at https://github.com/JieGong1130/MFEE-dataset. The code can be found at https://github.com/JieGong1130/MFEE-master. |
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| ISSN: | 2376-5992 |