2024
EACL
EACL 2024
Dependency Annotation of Ottoman Turkish with Multilingual BERT
Abstract
AbstractThis study introduces a pretrained large language model-based annotation methodology of the first dependency treebank in Ottoman Turkish. Our experimental results show that, through 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.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Deep Learning > Architectures > Transformers
Natural Language Processing > Understanding > Parsing
Natural Language Processing > Resources & Methods > Multilingual NLP
Natural Language Processing > Applications > Natural Language Inference
Artificial Intelligence > Core AI > Language
Deep Learning > Techniques > Transfer Learning