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    <titleInfo>
        <title>Representing Implicit Positive Meaning of Negated Statements in AMR</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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            <title>Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop</title>
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        <name type="personal">
            <namePart type="given">Claire</namePart>
            <namePart type="family">Bonial</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Nianwen</namePart>
            <namePart type="family">Xue</namePart>
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        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>Abstract Meaning Representation (AMR) has become popular for representing the meaning of natural language in graph structures. However, AMR does not represent scope information, posing a problem for its overall expressivity and specifically for drawing inferences from negated statements. This is the case with so-called “positive interpretations” of negated statements, in which implicit positive meaning is identified by inferring the opposite of the negation’s focus. In this work, we investigate how potential positive interpretations (PPIs) can be represented in AMR. We propose a logically motivated AMR structure for PPIs that makes the focus of negation explicit and sketch an initial proposal for a systematic methodology to generate this more expressive structure.</abstract>
    <identifier type="citekey">stein-donatelli-2021-representing</identifier>
    <identifier type="doi">10.18653/v1/2021.law-1.3</identifier>
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        <url>https://aclanthology.org/2021.law-1.3</url>
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        <date>2021-11</date>
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            <start>23</start>
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%0 Conference Proceedings
%T Representing Implicit Positive Meaning of Negated Statements in AMR
%A Stein, Katharina
%A Donatelli, Lucia
%Y Bonial, Claire
%Y Xue, Nianwen
%S Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F stein-donatelli-2021-representing
%X Abstract Meaning Representation (AMR) has become popular for representing the meaning of natural language in graph structures. However, AMR does not represent scope information, posing a problem for its overall expressivity and specifically for drawing inferences from negated statements. This is the case with so-called “positive interpretations” of negated statements, in which implicit positive meaning is identified by inferring the opposite of the negation’s focus. In this work, we investigate how potential positive interpretations (PPIs) can be represented in AMR. We propose a logically motivated AMR structure for PPIs that makes the focus of negation explicit and sketch an initial proposal for a systematic methodology to generate this more expressive structure.
%R 10.18653/v1/2021.law-1.3
%U https://aclanthology.org/2021.law-1.3
%U https://doi.org/10.18653/v1/2021.law-1.3
%P 23-35

Markdown (Informal)

[Representing Implicit Positive Meaning of Negated Statements in AMR](https://aclanthology.org/2021.law-1.3) (Stein & Donatelli, LAW 2021)

• Representing Implicit Positive Meaning of Negated Statements in AMR (Stein & Donatelli, LAW 2021)

ACL

• Katharina Stein and Lucia Donatelli. 2021. Representing Implicit Positive Meaning of Negated Statements in AMR. In Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, pages 23–35, Punta Cana, Dominican Republic. Association for Computational Linguistics.