<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wein-bonn-2023-comparing">
    <titleInfo>
        <title>Comparing UMR and Cross-lingual Adaptations of AMR</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Shira</namePart>
        <namePart type="family">Wein</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Julia</namePart>
        <namePart type="family">Bonn</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Fourth International Workshop on Designing Meaning Representations</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Julia</namePart>
            <namePart type="family">Bonn</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Nianwen</namePart>
            <namePart type="family">Xue</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Nancy, France</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Abstract Meaning Representation (AMR) is a popular semantic annotation schema that presents sentence meaning as a graph while abstracting away from syntax. It was originally designed for English, but has since been extended to a variety of non-English versions of AMR. These cross-lingual adaptations, to varying degrees, incorporate language-specific features necessary to effectively capture the semantics of the language being annotated. Uniform Meaning Representation (UMR) on the other hand, the multilingual extension of AMR, was designed specifically for cross-lingual applications. In this work, we discuss these two approaches to extending AMR beyond English. We describe both approaches, compare the information they capture for a case language (Spanish), and outline implications for future work.</abstract>
    <identifier type="citekey">wein-bonn-2023-comparing</identifier>
    <location>
        <url>https://aclanthology.org/2023.dmr-1.3</url>
    </location>
    <part>
        <date>2023-06</date>
        <extent unit="page">
            <start>23</start>
            <end>33</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Comparing UMR and Cross-lingual Adaptations of AMR
%A Wein, Shira
%A Bonn, Julia
%Y Bonn, Julia
%Y Xue, Nianwen
%S Proceedings of the Fourth International Workshop on Designing Meaning Representations
%D 2023
%8 June
%I Association for Computational Linguistics
%C Nancy, France
%F wein-bonn-2023-comparing
%X Abstract Meaning Representation (AMR) is a popular semantic annotation schema that presents sentence meaning as a graph while abstracting away from syntax. It was originally designed for English, but has since been extended to a variety of non-English versions of AMR. These cross-lingual adaptations, to varying degrees, incorporate language-specific features necessary to effectively capture the semantics of the language being annotated. Uniform Meaning Representation (UMR) on the other hand, the multilingual extension of AMR, was designed specifically for cross-lingual applications. In this work, we discuss these two approaches to extending AMR beyond English. We describe both approaches, compare the information they capture for a case language (Spanish), and outline implications for future work.
%U https://aclanthology.org/2023.dmr-1.3
%P 23-33

Markdown (Informal)

[Comparing UMR and Cross-lingual Adaptations of AMR](https://aclanthology.org/2023.dmr-1.3) (Wein & Bonn, DMR-WS 2023)

• Comparing UMR and Cross-lingual Adaptations of AMR (Wein & Bonn, DMR-WS 2023)

ACL

• Shira Wein and Julia Bonn. 2023. Comparing UMR and Cross-lingual Adaptations of AMR. In Proceedings of the Fourth International Workshop on Designing Meaning Representations, pages 23–33, Nancy, France. Association for Computational Linguistics.