A Feature-Rich Vietnamese Named-Entity Recognition Model
Table 4: Accuracy of our NER system with default and generated PoS, chunking tags; and without PoS and chunking tags
['[BOLD] Setting', '[BOLD] Precision', '[BOLD] Recall', '[ITALIC] F1']
We can see that with automatically-generated PoS and chunking tags, F1 score of the system dropped significantly, which is 4.63%. Incorporating automatically generated PoS and chunk by tools NNVLP or Underthesea did not improve the accuracy of the NER model. Underthesea tool showed the better result than NNVLP when they were used in our NER model.