This study introduces a pretrained large language model-based annotation
methodology for the first dependency treebank in Ottoman Turkish. Our
experimental results show that, iteratively, i) pseudo-annotating data using a
multilingual BERT-based parsing model, ii) manually correcting the
pseudo-annotations, and iii) fine-tuning the parsing model with the corrected
annotations, we speed up and simplify the challenging dependency annotation
process. The resulting treebank, that will be a part of the Universal
Dependencies (UD) project, will facilitate automated analysis of Ottoman
Turkish documents, unlocking the linguistic richness embedded in this
historical heritage.

使用预先训练的大型语言模型进行注释方法的研究，针对奥斯曼土耳其语第一个依赖树库。实验结果表明，通过迭代使用多语言 BERT 解析模型进行伪标注数据，手动纠正伪注释以及使用纠正的注释对解析模型进行微调，我们加快了并简化了具有挑战性的依赖注释过程。生成的树库将成为通用依赖项目的一部分，将有助于解锁奥斯曼土耳其语历史遗产中蕴含的语言丰富性，从而实现奥斯曼土耳其语文档的自动化分析。