@inproceedings{lin-etal-2024-automatic,
    title = "Automatic Construction of the {E}nglish Sentence Pattern Structure Treebank for {C}hinese {ESL} learners",
    author = "Zhu, Lin  and
      Xu, Meng  and
      Guo, Wenya  and
      Yu, Jingsi  and
      Yang, Liner  and
      Cao, Zehuang  and
      Huang, Yuan  and
      Yang, Erhong",
    editor = "Maosong, Sun  and
      Jiye, Liang  and
      Xianpei, Han  and
      Zhiyuan, Liu  and
      Yulan, He",
    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/author-degibert/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.''"
}