Lung-Hao Lee, Tzu-Mi Lin, and Chao-Yi Chen.
In Proceedings of the 35th Conference on Computational Linguistics and Speech Processing (ROCLING’23), pages 333-338.
Abstract
This paper describes the ROCLING-2023 shared task for Chinese multi-genre named entity recognition in the healthcare domain, including task description, data preparation, performance metrics, and evaluation results. Among eight registered teams, six participating teams submitted a total of 16 runs. This shared task demonstrates current NLP techniques for dealing with Chinese named entity recognition in multi-genre texts. All data sets with gold standards and evaluation scripts used in this shared task are publicly available for future research.