Mapping AMR to UMR: Resources for Adapting Existing Corpora for Cross-Lingual Compatibility

Autor
Bonn, Julia
Myers, Skatje
Van Gysel, Jens E.L.
Denk, Lukas
Vigus, Meagan
Zhao, Jin
Cowell, Andrew
Croft, William
Martin, James H.
Palmer, Alexis
Palmer, Martha
Pustejovsky, James
Vallejos, Rosa
Xue, Nianwen
Association for Computational Linguistics
Datum vydání
2023Publikováno v
TLT 2023 - 21st International Workshop on Treebanks and Linguistic Theories (TLT, GURT/SyntaxFest 2023), Proceedings of the ConferenceNakladatel / Místo vydání
Association for Computational Linguistics (Washington, D.C., USA)Ročník / Číslo vydání
21ISBN / ISSN
ISBN: 978-1-959429-33-3Metadata
Zobrazit celý záznamKolekce
Abstrakt
This paper presents detailed mappings between the structures used in Abstract Meaning Representation (AMR) and those used in Uniform Meaning Representation (UMR). These structures include general semantic roles, rolesets, and concepts that are largely shared between AMR and UMR, but with crucial differences. While UMR annotation of new low-resource languages is ongoing, AMR-annotated corpora already exist for many languages, and these AMR corpora are ripe for conversion to UMR format. Rather than focusing on semantic coverage that is new to UMR (which will likely need to be dealt with manually), this paper serves as a resource (with illustrated mappings) for users looking to understand the fine-grained adjustments that have been made to the representation techniques for semantic categories present in both AMR and UMR.
Klíčová slova
abstract meaning representation, uniform meaning representation, corpus, semantics
Trvalý odkaz
https://hdl.handle.net/20.500.14178/2335Licence
Licence pro užití plného textu výsledku: Creative Commons Uveďte původ 4.0 International