Assessing the Cross-linguistic Utility of Abstract Meaning Representation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AEZW9RUL2" target="_blank" >RIV/00216208:11320/25:EZW9RUL2 - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194465811&doi=10.1162%2fcoli_a_00503&partnerID=40&md5=eb5d1b37f161660a6a3af954585c22cc" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194465811&doi=10.1162%2fcoli_a_00503&partnerID=40&md5=eb5d1b37f161660a6a3af954585c22cc</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1162/coli_a_00503" target="_blank" >10.1162/coli_a_00503</a>

Result language

angličtina

Original language name

Assessing the Cross-linguistic Utility of Abstract Meaning Representation

Original language description

Semantic representations capture the meaning of a text. Abstract Meaning Representation (AMR), a type of semantic representation, focuses on predicate-argument structure and abstracts away from surface form. Though AMR was developed initially for English, it has now been adapted to a multitude of languages in the form of non-English annotation schemas, cross-lingual text-to-AMR parsing, and AMR-to-(non-English) text generation. We advance prior work on cross-lingual AMR by thoroughly investigating the amount, types, and causes of differences that appear in AMRs of different languages. Further, we compare how AMR captures meaning in cross-lingual pairs versus strings, and show that AMR graphs are able to draw out fine-grained differences between parallel sentences. We explore three primary research questions: (1) What are the types and causes of differences in parallel AMRs? (2) How can we measure the amount of difference between AMR pairs in different languages? (3) Given that AMR structure is affected by language and exhibits cross-lingual differences, how do cross-lingual AMR pairs compare to string-based representations of cross-lingual sentence pairs? We find that the source language itself does have a measurable impact on AMR structure, and that translation divergences and annotator choices also lead to differences in cross-lingual AMR pairs. We explore the implications of this finding throughout our study, concluding that, although AMR is useful to capture meaning across languages, evaluations need to take into account source language influences if they are to paint an accurate picture of system output, and meaning generally. © 2024 Association for Computational Linguistics.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computational Linguistics

ISSN

0891-2017

e-ISSN

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Volume of the periodical

50

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

55

Pages from-to

419-473

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85194465811