"This paper presents a review of CCL2025-Eval Task 5: Appreciation Evaluation (CCPA). The primary aim of this task is to evaluate the ability of lan-guage models in performing deep semantic understanding and aesthetic appreciation of Chinese classical poetry. The evaluation comprises two tracks: (1) Poetic content understanding, which examines models’ ability to interpret both fine-grained and coarse-grained semantics; (2) Poetic emotion recognition, which evaluates models’ capacity to identify and analyze emotional expressions. A total of 55 teams registered for the task, among which 7 teams provided valid submissions. The paper provides an in-depth analysis of the submissions and results from all participating teams."

“本文介绍了我们在第二十三届中文计算语言学大会中文抽象语义表示解析评测任务中提交的参赛系统。中文抽象语义表示(Chinese Abstract Meaning Representa-tion,CAMR)以一个单根可遍历的有向无环图表示中文句子的语义。本系统选择大语言模型作为解决方案。我们首先系统地评估了当下中文大语言模型在AMR解析任务上的性能,在此基础上基于图融合算法整合性能较高的大模型预测结果,最终得到预测的CAMR图。实验结果表明,1)现有大模型已经具备一定的少样本中文AMR解析能力;2)基于微调中文大模型的AMR解析系统能够取得相较以往最优系统更强的性能;3)图融合算法能够进一步增强基于大模型的CAMR解析系统的性能。”