Bootstrapping UMRs from Universal Dependencies for Scalable Multilingual Annotation

Uniform Meaning Representation (UMR) is a semantic annotation framework designed to be applicable across typologically diverse languages.However, UMR annotation is a laborintensive task, requiring significant effort and time especially when no prior annotations are available.In this paper, we present a method for bootstrapping UMR graphs by leveraging Universal Dependencies (UD), one of the most comprehensive multilingual resources, encompassing languages across a wide range of language families.Given UMR's strong typological and cross-linguistic orientation, UD serves as a particularly suitable starting point for the conversion.We describe and evaluate an approach that automatically derives partial UMR graphs from UD trees, providing annotators with an initial representation to build upon.While UD is not a semantic resource, our method extracts useful structural information that aligns with the UMR formalism, thereby facilitating the annotation process.By leveraging UD's broad typological coverage, this approach offers a scalable way to support UMR annotation across different languages.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.law-1.10
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Bootstrapping UMRs from Universal Dependencies for Scalable Multilingual Annotation

Federica Gamba, Daniel Zeman, Alexis Palmer
Natural Language Processing Techniques
article

Bootstrapping UMRs from Universal Dependencies for Scalable Multilingual Annotation

Federica Gamba, Daniel Zeman, Alexis Palmer
article en

Abstract

Uniform Meaning Representation (UMR) is a semantic annotation framework designed to be applicable across typologically diverse languages.However, UMR annotation is a laborintensive task, requiring significant effort and time especially when no prior annotations are available.In this paper, we present a method for bootstrapping UMR graphs by leveraging Universal Dependencies (UD), one of the most comprehensive multilingual resources, encompassing languages across a wide range of language families.Given UMR's strong typological and cross-linguistic orientation, UD serves as a particularly suitable starting point for the conversion.We describe and evaluate an approach that automatically derives partial UMR graphs from UD trees, providing annotators with an initial representation to build upon.While UD is not a semantic resource, our method extracts useful structural information that aligns with the UMR formalism, thereby facilitating the annotation process.By leveraging UD's broad typological coverage, this approach offers a scalable way to support UMR annotation across different languages.

National Science Foundation, Univerzita Karlova v Praze, Grantová Agentura České Republiky, Division of Computer and Network Systems
Openalex Percentile: Top 90%
Natural Language Processing Techniques
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Bootstrapping UMRs from Universal Dependencies for Scalable Multilingual Annotation — Federica Gamba, Daniel Zeman, et al. · (2025) | TGRS Research Map | TGRS