Extending Uniform Meaning Representation to Persian: The First Corpus Resource

Abstract

Uniform Meaning Representation (UMR) has cross-linguistic design principles that make it particularly well-suited as a semantic representation framework for capturing all language-specific phenomena. Despite its growing adoption, no UMR corpus currently exists for Persian. In this paper, we present the first version of a Persian UMR dataset created through a rule-based conversion of existing Persian AMR annotations from The Little Prince corpus, followed by manual mapping of split semantic roles from AMR to their finer-grained UMR counterparts. We report detailed statistics on the conversion, analyze the challenges of mapping Persian AMR structures into UMR, and provide illustrative examples. The resource is freely available and it lays the groundwork for subsequent enrichment of Persian UMR with additional semantic layers, including co-reference, named entities, and discourse relations.

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