  The Yunshan Cup 2020 track focused on creating a framework for evaluating
different methods of part-of-speech (POS). There were two tasks for this track:
(1) POS tagging for the Indonesian language, and (2) POS tagging for the Lao
tagging. The Indonesian dataset is comprised of 10000 sentences from Indonesian
news within 29 tags. And the Lao dataset consists of 8000 sentences within 27
tags. 25 teams registered for the task. The methods of participants ranged from
feature-based to neural networks using either classical machine learning
techniques or ensemble methods. The best performing results achieve an accuracy
of 95.82% for Indonesian and 93.03%, showing that neural sequence labeling
models significantly outperform classic feature-based methods and rule-based
methods.
