Xiaojuan Tan
2026
Examining Large Language Models’ form-meaning mappings of information structure constructions in Mandarin Chinese
Shihui Li | Xiaojuan Tan | Jelke Bloem
Proceedings of the 30th Conference on Computational Natural Language Learning
Shihui Li | Xiaojuan Tan | Jelke Bloem
Proceedings of the 30th Conference on Computational Natural Language Learning
Construction Grammar (CxG) knowledge in language models has been extensively studied for English, but remains underexplored in other languages. In Mandarin Chinese, the ba (把, disposal) and 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 ba construction, although they achieve high accuracy on paradigms driven by surface syntactic cues.
2024
Broadening the coverage of computational representations of metaphor through Dynamic Metaphor Theory
Xiaojuan Tan | Jelke Bloem
Proceedings of the First Workshop on Reference, Framing, and Perspective @ LREC-COLING 2024
Xiaojuan Tan | Jelke Bloem
Proceedings of the First Workshop on Reference, Framing, and Perspective @ LREC-COLING 2024
Current approaches to computational metaphor processing typically incorporate static representations of metaphor. We aim to show that this limits the coverage of such systems. We take insights from dynamic metaphor theory and discuss how existing computational models of metaphor might benefit from representing the dynamics of metaphor when applied to the analysis of conflicting discourse. We propose that a frame-based approach to metaphor representation based on the model of YinYang Dynamics of Metaphoricity (YYDM) would pave the way to more comprehensive modeling of metaphor. In particular, the metaphoricity cues of the YYDM model could be used to address the task of dynamic metaphor identification. Frame-based modeling of dynamic metaphor would facilitate the computational analysis of perspectives in conflicting discourse, with potential applications in analyzing political discourse.