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        <title>From Sentence to Action: Splitting AMR Graphs for Recipe Instructions</title>
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    <name type="personal">
        <namePart type="given">Katharina</namePart>
        <namePart type="family">Stein</namePart>
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    <name type="personal">
        <namePart type="given">Lucia</namePart>
        <namePart type="family">Donatelli</namePart>
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    <name type="personal">
        <namePart type="given">Alexander</namePart>
        <namePart type="family">Koller</namePart>
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            <title>Proceedings of the Fourth International Workshop on Designing Meaning Representations</title>
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            <namePart type="given">Julia</namePart>
            <namePart type="family">Bonn</namePart>
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        <name type="personal">
            <namePart type="given">Nianwen</namePart>
            <namePart type="family">Xue</namePart>
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    <abstract>Accurately interpreting the relationships between actions in a recipe text is essential to successful recipe completion. We explore using Abstract Meaning Representation (AMR) to represent recipe instructions, abstracting away from syntax and sentence structure that may order recipe actions in arbitrary ways. We present an algorithm to split sentence-level AMRs into action-level AMRs for individual cooking steps. Our approach provides an automatic way to derive fine-grained AMR representations of actions in cooking recipes and can be a useful tool for downstream, instructional tasks.</abstract>
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%0 Conference Proceedings
%T From Sentence to Action: Splitting AMR Graphs for Recipe Instructions
%A Stein, Katharina
%A Donatelli, Lucia
%A Koller, Alexander
%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 stein-etal-2023-sentence
%X Accurately interpreting the relationships between actions in a recipe text is essential to successful recipe completion. We explore using Abstract Meaning Representation (AMR) to represent recipe instructions, abstracting away from syntax and sentence structure that may order recipe actions in arbitrary ways. We present an algorithm to split sentence-level AMRs into action-level AMRs for individual cooking steps. Our approach provides an automatic way to derive fine-grained AMR representations of actions in cooking recipes and can be a useful tool for downstream, instructional tasks.
%U https://aclanthology.org/2023.dmr-1.6
%P 52-67

Markdown (Informal)

[From Sentence to Action: Splitting AMR Graphs for Recipe Instructions](https://aclanthology.org/2023.dmr-1.6) (Stein et al., DMR-WS 2023)

• From Sentence to Action: Splitting AMR Graphs for Recipe Instructions (Stein et al., DMR-WS 2023)

ACL

• Katharina Stein, Lucia Donatelli, and Alexander Koller. 2023. From Sentence to Action: Splitting AMR Graphs for Recipe Instructions. In Proceedings of the Fourth International Workshop on Designing Meaning Representations, pages 52–67, Nancy, France. Association for Computational Linguistics.