Vietnamese Named Entity Recognition using Token Regular Expressions and Bidirectional Inference
This work addresses named entity recognition for Vietnamese, an incremental improvement in a domain-specific task.
The paper tackled Vietnamese named entity recognition by combining token regular expressions and bidirectional inference in a sequence labeling model, achieving an F1 score of 89.66% on a VLSP test set.
This paper describes an efficient approach to improve the accuracy of a named entity recognition system for Vietnamese. The approach combines regular expressions over tokens and a bidirectional inference method in a sequence labelling model. The proposed method achieves an overall $F_1$ score of 89.66% on a test set of an evaluation campaign, organized in late 2016 by the Vietnamese Language and Speech Processing (VLSP) community.