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Vietnamese NER Using Bi-LSTM and CRF by Mehari Yohannes is a document available to read on EtoBox.

What is Vietnamese NER Using Bi-LSTM and CRF about?

This document presents a deep learning model for Vietnamese named entity recognition (NER) that combines bidirectional long short-term memory (Bi-LSTM) and conditional random fields (CRF). The model uses character-level embeddings from a Bi-LSTM combined with part-of-speech and chunk features as input to a CRF output layer. Evaluation on a Vietnamese dataset achieves a new state-of-the-art F1 score of 95.61% for Vietnamese NER.

Author

Mehari Yohannes

Language

EN