A Feature-Rich Vietnamese Named-Entity Recognition Model
Table 3: Accuracy of our NER system with full features set and default PoS and chunking tags
['[BOLD] System', '[BOLD] Precision', '[BOLD] Recall', '[ITALIC] F1']
In experiments, we use micro-averaged F1 score, the official evaluation metric in CoNLL 2003 We compare our NER model with following Vietnamese NER models. We obtain 93.93% of F1 score on the test set, which is 1% higher than NNVLP system.