这篇论文拿粤语和爱尔兰语试了gpt-oss-120b，翻译和句法生成都不太靠谱，但能给你点备选分析思路。
该论文报告了ParGram项目中粤语与爱尔兰语树库的开发，在抽象功能层面维持跨语言平行性。作者测试了OpenAI gpt-oss-120b模型辅助语法工程，包括粤语-爱尔兰语翻译与句法结构生成。结果显示翻译质量整体不佳，且不受提示语言影响；结构生成虽产出部分有效分析，但跨语言抽象任务表现较差。论文认为LLM输出可作为备选分析参考，但专家验证仍不可替代。
Grammar Engineering Meets LLMs: Development of Cantonese and Irish ParGram Treebanks
Grammar engineering requires expertise in linguistic formalism and computational implementation, especially in parallel grammar projects that balance cross-linguistic consistency with language-specific properties. This paper presents the development of Cantonese and Irish treebanks within the Parallel Grammar (ParGram) Project, where linguistic parallelism is maintained at an abstract functional level. We also investigate the methodological potential and limitations of using multilingual LLMs to support grammar engineering, focusing on Cantonese-Irish translation and the generation of formal syntactic structures using OpenAI's gpt-oss-120b model. The results show that translation performance was generally unsatisfactory and unaffected by prompt language. For syntactic structure generation, the model produced some structurally meaningful outputs, but performed poorly on tasks requiring cross-linguistic abstraction. Nonetheless, LLM-generated outputs may still offer some reference value by suggesting alternative analyses and (partially) capturing predicate-argument relations. Overall, our findings highlight both the potential and limitations of using LLMs in collaborative grammar engineering, while underscoring the continued importance of expert-driven analysis and verification.