LSTM Easy-first Dependency Parsing with Pre-trained Word Embeddings and Character-level Word Embeddings in Vietnamese
Computation and Language
2019-10-31 v1
Abstract
In Vietnamese dependency parsing, several methods have been proposed. Dependency parser which uses deep neural network model has been reported that achieved state-of-the-art results. In this paper, we proposed a new method which applies LSTM easy-first dependency parsing with pre-trained word embeddings and character-level word embeddings. Our method achieves an accuracy of 80.91% of unlabeled attachment score and 72.98% of labeled attachment score on the Vietnamese Dependency Treebank (VnDT).
Keywords
Cite
@article{arxiv.1910.13732,
title = {LSTM Easy-first Dependency Parsing with Pre-trained Word Embeddings and Character-level Word Embeddings in Vietnamese},
author = {Binh Duc Nguyen and Kiet Van Nguyen and Ngan Luu-Thuy Nguyen},
journal= {arXiv preprint arXiv:1910.13732},
year = {2019}
}