@inproceedings{liu-etal-2025-system,
    title = "System Report for {CCL}25-Eval Task 2: Enhanced {C}hinese Frame Semantic Parsing with Pre-trained Model and Linguistic Features",
    author = "Liu, Yahui  and
      Qiao, Ziheng  and
      Gong, Chen  and
      Zhang, Min",
    editor = "Lin, Hongfei  and
      Li, Bin  and
      Tan, Hongye",
    booktitle = "Proceedings of the 24th {C}hina National Conference on Computational Linguistics ({CCL} 2025)",
    month = aug,
    year = "2025",
    address = "Jinan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/ingest-ccl/2025.ccl-2.5/",
    pages = "47--54",
    abstract = "``This paper presents our system submitted to the Chinese Frame Semantic Parsing evaluation task at the 24th China National Conference on Computational Linguistics (CCL2025). For the three subtasks of Frame Identification (FI), Argument Identification (AI), and Role Identification(RI), we utilized a larger Chinese pre-trained model, as the foundation and adopted specific optimization strategies for FI and RI subtasks. Specifically, we incorporated word segmentation structure information and updatable pre-trained target word embeddings in the FI subtask, and explored the use of Focal Loss combined with target word embeddings and word segmentation structure information in the RI subtask. Furthermore, a voting mechanism was employed in both the FI and RI subtasks to enhance performance. Our system ultimately achieved first place on the TestA and second place on the TestB.''"
}