@inproceedings{im-lee-2024-gpt,
    title = "What {GPT}-4 Knows about Aspectual Coercion: Focused on ``Begin the Book''",
    author = "Im, Seohyun  and
      Lee, Chungmin",
    editor = "Zock, Michael  and
      Chersoni, Emmanuele  and
      Hsu, Yu-Yin  and
      de Deyne, Simon",
    booktitle = "Proceedings of the Workshop on Cognitive Aspects of the Lexicon @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.cogalex-1.7/",
    pages = "56--67",
    abstract = "This paper explores whether Pre-trained Large Language Models (PLLMs) like GPT-4 can grasp profound linguistic insights into language phenomena such as Aspectual Coercion through interaction with Microsoft{'}s Copilot, which integrates GPT-4. Firstly, we examined Copilot{'}s understanding of the co-occurrence constraints of the aspectual verb ``begin'' and the complex-type noun ``book'' using the classic illustration of Aspectual Coercion, ``begin the book.'' Secondly, we verified Copilot{'}s awareness of both the default interpretation of ``begin the book'' with no specific context and the contextually preferred interpretation. Ultimately, Copilot provided appropriate responses regarding potential interpretations of ``begin the book'' based on its distributional properties and context-dependent preferred interpretations. However, it did not furnish sophisticated explanations concerning these interpretations from a linguistic theoretical perspective. On the other hand, by offering diverse interpretations grounded in distributional properties, language models like GPT-4 demonstrated their potential contribution to the refinement of linguistic theories. Furthermore, we suggested the feasibility of employing Language Models to construct language resources associated with language phenomena including Aspectual Coercion."
}