Year: 2025
Type: conference-paper
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.
Source: Linguistic Annotation Workshop
Authors: Federica Gamba, Alexis Palmer, Daniel Zeman
Institutions: Charles University, University of Colorado Boulder
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412944306