Dependency Annotation of Ottoman Turkish with Multilingual BERT
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Abstract (arXiv)
This study introduces a pretrained large language model-based annotation methodology for the first de dency 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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 16 references that are in the map. First posted on arXiv 22 Feb 2024.
Builds on
6 of 16 references.
References · 6
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019Towards Making the Most of BERT in Neural Machine Translationcited by 43
- 2021Generate, Annotate, and Learn: NLP with Synthetic Textcited by 42
- 2020Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessarycited by 8
- 2020Resources for Turkish Dependency Parsing: Introducing the BOUN Treebank and the BoAT Annotation Toolcited by 7
- 2021Iterative Pseudo-Labeling with Deep Feature Annotation and Confidence-Based Samplingcited by 4
Built on by
Citing papers per year: 2025: 2; 2026: 1.
3 papers.