@inproceedings{lin-etal-2024-automatic,
    title = "Automatic Construction of the {E}nglish Sentence Pattern Structure Treebank for {C}hinese {ESL} learners",
    author = "Lin, Zhu  and
      Meng, Xu  and
      Wenya, Guo  and
      Jingsi, Yu  and
      Liner, Yang  and
      Zehuang, Cao  and
      Yuan, Huang  and
      Erhong, Yang",
    editor = "Sun, Maosong  and
      Liang, Jiye  and
      Han, Xianpei  and
      Liu, Zhiyuan  and
      He, Yulan",
    booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)",
    month = jul,
    year = "2024",
    address = "Taiyuan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.ccl-1.95/",
    pages = "1223--1238",
    language = "eng",
    abstract = "``Analyzing long and complicated sentences has always been a priority and challenge in Englishlearning. In order to conduct the parse of these sentences for Chinese English as Second Lan-guage (ESL) learners, we design the English Sentence Pattern Structure (ESPS) based on theSentence Diagramming theory. Then, we automatically construct the English Sentence PatternStructure Treebank (ESPST) through the method of rule conversion based on constituency struc-ture and evaluate the conversion results. In addition, we set up two comparative experiments,using trained parser and large language models (LLMs). The results prove that the rule-basedconversion approach is effective.''"
}