Antibiotic resistance event extraction involves the automated extraction of information related to antibiotic resistance mechanisms from a vast amount of biomedical literature. This can be achieved by utilizing natural language processing techniques. However, the distinctive characteristics of the biomedical field lead to various challenges for existing antibiotic resistance event extraction methods, such as limited labeling data, complex names of biomedical entities, and nesting and overlapping event structures. These factors make it challenging to apply the current processing methods for bio...
