Developing a Universal Dependencies Treebank for Ukrainian Parliamentary Speech

This paper presents a new Universal Dependencies (UD) treebank based on Ukrainian parliamentary transcripts, complementing the existing UD resources for Ukrainian.The corpus includes manually annotated texts from key historical sessions of the Verkhovna Rada, capturing not only official rhetoric but also features of colloquial spoken language.The annotation combines UDPipe2 and TagText parsers, with subsequent manual correction to ensure syntactic and morphological accuracy.A detailed comparison of tagsets and the disambiguation strategy employed by TagText is provided.To demonstrate the applicability of the resource, the study examines vocative and nominative case variation in direct address using a largescale UD-annotated corpus of parliamentary texts.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.unlp-1.7
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Developing a Universal Dependencies Treebank for Ukrainian Parliamentary Speech

Andriy Rysin, Maria Shvedova, Arsenii Lukashevskyi
Natural Language Processing Techniques
article

Developing a Universal Dependencies Treebank for Ukrainian Parliamentary Speech

Andriy Rysin, Maria Shvedova, Arsenii Lukashevskyi
article en

Abstract

This paper presents a new Universal Dependencies (UD) treebank based on Ukrainian parliamentary transcripts, complementing the existing UD resources for Ukrainian.The corpus includes manually annotated texts from key historical sessions of the Verkhovna Rada, capturing not only official rhetoric but also features of colloquial spoken language.The annotation combines UDPipe2 and TagText parsers, with subsequent manual correction to ensure syntactic and morphological accuracy.A detailed comparison of tagsets and the disambiguation strategy employed by TagText is provided.To demonstrate the applicability of the resource, the study examines vocative and nominative case variation in direct address using a largescale UD-annotated corpus of parliamentary texts.

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Natural Language Processing Techniques
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