NNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit
This provides a practical toolkit for Vietnamese NLP researchers and developers, though it is incremental as it combines existing methods.
The authors tackled essential Vietnamese language processing tasks by developing NNVLP, a neural network-based toolkit that achieves state-of-the-art results on part-of-speech tagging, chunking, and named entity recognition.
This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity recognition (NER). Our toolkit is a combination of bidirectional Long Short-Term Memory (Bi-LSTM), Convolutional Neural Network (CNN), Conditional Random Field (CRF), using pre-trained word embeddings as input, which achieves state-of-the-art results on these three tasks. We provide both API and web demo for this toolkit.