@inproceedings{li-etal-2026-examining,
    title = "Examining Large Language Models' form-meaning mappings of information structure constructions in {M}andarin {C}hinese",
    author = "Li, Shihui  and
      Tan, Xiaojuan  and
      Bloem, Jelke",
    editor = "Bonial, Claire  and
      Berzak, Yevgeni",
    booktitle = "Proceedings of the 30th Conference on Computational Natural Language Learning",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.conll-main.37/",
    pages = "613--625",
    ISBN = "979-8-89176-410-1",
    abstract = "Construction Grammar (CxG) knowledge in language models has been extensively studied for English, but remains underexplored in other languages. In Mandarin Chinese, the \textit{ba} (把, disposal) and \textit{bei} (被, passive) constructions are widely used for managing information structure. They foreground topical elements (information structure) and encode systematic form-meaning mappings (CxG), particularly with respect to the semantic role of the object. We probe language models' linguistic competence with these constructions using minimal pairs, constructing a new minimal-pair dataset comprising seven paradigms that target both syntactic constraints and verb{--}construction compatibility. Our results show that it remains a challenge for many models to capture the form-meaning mappings underlying the \textit{ba} construction, although they achieve high accuracy on paradigms driven by surface syntactic cues."
}