Urdu Dependency Parsing and Treebank Development: A Syntactic and Morphological Perspective

• URL: http://arxiv.org/abs/2406.09549v2
• Date: Wed, 02 Oct 2024 11:44:26 GMT
• Title: Urdu Dependency Parsing and Treebank Development: A Syntactic and Morphological Perspective
• Authors: Nudrat Habib,
• Abstract summary: We use dependency parsing to analyze news articles in Urdu. We achieve a best-labeled accuracy (LA) of 70% and an unlabeled attachment score (UAS) of 84%.
• Score: 0.0
• License:
• Abstract: 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.

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