论文标题
一项针对越南选区解析的实证研究，并进行预培训
An Empirical Study for Vietnamese Constituency Parsing with Pre-training
论文作者
论文摘要
在这项工作中，我们使用基于跨度的方法进行越南选区解析。我们的方法遵循使用CKY式推理算法的自我发项编码器结构和图表解码器。我们介绍了使用培训前XLM-ROBERTA和PHOBERT在越南数据集viettreebank和NiivtB1上使用训练模型XLM-Roberta和Phobert进行经验方法的实验结果的分析。结果表明，我们使用XLM-Roberta的模型归档了明显的F1得分，比其他训练前模型更好，ViettreeBank为81.19％，NIIVTB1为85.70％。
In this work, we use a span-based approach for Vietnamese constituency parsing. Our method follows the self-attention encoder architecture and a chart decoder using a CKY-style inference algorithm. We present analyses of the experiment results of the comparison of our empirical method using pre-training models XLM-Roberta and PhoBERT on both Vietnamese datasets VietTreebank and NIIVTB1. The results show that our model with XLM-Roberta archived the significantly F1-score better than other pre-training models, VietTreebank at 81.19% and NIIVTB1 at 85.70%.
