Urdu Dependency Parsing and Treebank Development: A Syntactic and Morphological Perspective
<|reference_start|>Urdu Dependency Parsing and Treebank Development: A Syntactic and Morphological Perspective: Parsing is the process of analyzing a sentence's syntactic structure by breaking it down into its grammatical components. and is critical for various linguistic applications. Urdu is a low-resource, free word-order language and exhibits complex morphology. Literature suggests that dependency parsing is well-suited for such languages. Our approach begins with a basic feature model encompassing word location, head word identification, and dependency relations, followed by a more advanced model integrating part-of-speech (POS) tags and morphological attributes (e.g., suffixes, gender). We manually annotated a corpus of news articles of varying complexity. Using Maltparser and the NivreEager algorithm, we achieved a best-labeled accuracy (LA) of 70% and an unlabeled attachment score (UAS) of 84%, demonstrating the feasibility of dependency parsing for Urdu.<|reference_end|>
@article{habib2024urdu,
    title={Urdu Dependency Parsing and Treebank Development: A Syntactic and
  Morphological Perspective},
    author={Nudrat Habib},
    journal={arXiv preprint arXiv:2406.09549},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.09549},
    primaryClass={cs.CL cs.LG}
}