mlsanityData to 7 Oct 2026

Dependency Annotation of Ottoman Turkish with Multilingual BERT

arXiv 2402.14743 ↗First posted 22 Feb 2024cs.CLcited by 3

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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

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Towards Making the Most of BERT in Neural Machine Translationcited by 43
  3. 2021Generate, Annotate, and Learn: NLP with Synthetic Textcited by 42
  4. 2020Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessarycited by 8
  5. 2020Resources for Turkish Dependency Parsing: Introducing the BOUN Treebank and the BoAT Annotation Toolcited by 7
  6. 2021Iterative Pseudo-Labeling with Deep Feature Annotation and Confidence-Based Samplingcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.