The results show that the model GRU+SVM with ELMo yields the best performance of 73.03% on the development data, while the model GRU+SVM with ELMo+POS outperforms all the other models on the test dataset with a micro-average F1 score of 69.93%, by being marginally better than GRU+SVM with ELMo 7 .
equations 4 and 5 show the mechanisms used to calculate the weights, where w corresponds to the weights in the single-layer neural network, and ν t is the single value, which is the result of feeding y t to the fully-connected layer.