Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text
TABLE II: Comparisons with the different methods on the task of NER
['Methods', 'NER Precision', 'NER Recall', 'NER F{}_{1}-score']
Based on NER, we experimentally compare our focused attention model with other reference algorithms. These algorithms consist of two NER models in medical domain (i.e., Bi-LSTM [gridach2017character] and RDCNN [qiu2019chinese]) and one joint model in generic domain (i.e., Joint-Bi-LSTM [zheng2017joint]). In addition, we originally plan to use the joint model [li2017neural] in the medical domain, but the character-level representations cannot be implemented in Chinese. Therefore, we replace it with a generic domain model [zheng2017joint] in similar structure.