Quantification in Abstract Meaning Representation

Kiyong Lee; Chongwon Park

doi:10.63317/5nkejg7f845v

Quantification in Abstract Meaning Representation

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Abstract

Quantification is common in text, but it is underrepresented in AMR. Quantification also stresses the common conjunctive interpretation of AMR graphs, since universal quantification introduces scope-taking structure and variable binding that cannot be captured as a flat list of conjuncts. We propose an enriched AMR that supports quantificational meaning while keeping AMR’s graph backbone. At the predicate level, we add QuantML features, such as domain restriction, determinacy, distributivity, and involvement. At the discourse level, we add contextual constraints that encode scope and other discourse-sensitive conditions. The two levels follow the UMR architecture and are linked by shared identifiers. We map the enriched graphs to two-block logical forms: a minimal model of events and participants, plus a constraint block that relates them.

Anthology ID:: 2026.slide-1.9
Volume:: Proceedings of the Workshop on Structured Linguistic Data and Evaluation (SLiDE)
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Erhard Hinrichs, Joakim Nivre, Petya Osenova, James Pustejovsky, Claus Zinn
Venues:: SLiDE | WS
SIG:
Publisher:: ELRA Language Resources Association (ELRA)
Note:
Pages:: 104–113
Language:
External URL:: https://lrec.elra.info/lrec2026-ws-slide-09
DOI:: 10.63317/5nkejg7f845v
Bibkey:
Cite (ACL):: Kiyong Lee and Chongwon Park. 2026. Quantification in Abstract Meaning Representation. In Proceedings of the Workshop on Structured Linguistic Data and Evaluation (SLiDE), pages 104–113, Palma de Mallorca, Spain. ELRA Language Resources Association (ELRA).
Cite (Informal):: Quantification in Abstract Meaning Representation (Lee & Park, SLiDE 2026)
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@inproceedings{lee-park-2026-quantification,
    title = "Quantification in {A}bstract {M}eaning {R}epresentation",
    author = "Lee, Kiyong  and
      Park, Chongwon",
    editor = "Hinrichs, Erhard  and
      Nivre, Joakim  and
      Osenova, Petya  and
      Pustejovsky, James  and
      Zinn, Claus",
    booktitle = "Proceedings of the Workshop on Structured Linguistic Data and Evaluation ({SL}i{DE})",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resources Association (ELRA)",
    url = "https://aclanthology.org/2026.slide-1.9/",
    doi = "10.63317/5nkejg7f845v",
    pages = "104--113",
    abstract = "Quantification is common in text, but it is underrepresented in AMR. Quantification also stresses the common conjunctive interpretation of AMR graphs, since universal quantification introduces scope-taking structure and variable binding that cannot be captured as a flat list of conjuncts. We propose an enriched AMR that supports quantificational meaning while keeping AMR{'}s graph backbone. At the predicate level, we add QuantML features, such as domain restriction, determinacy, distributivity, and involvement. At the discourse level, we add contextual constraints that encode scope and other discourse-sensitive conditions. The two levels follow the UMR architecture and are linked by shared identifiers. We map the enriched graphs to two-block logical forms: a minimal model of events and participants, plus a constraint block that relates them."
}

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%0 Conference Proceedings
%T Quantification in Abstract Meaning Representation
%A Lee, Kiyong
%A Park, Chongwon
%Y Hinrichs, Erhard
%Y Nivre, Joakim
%Y Osenova, Petya
%Y Pustejovsky, James
%Y Zinn, Claus
%S Proceedings of the Workshop on Structured Linguistic Data and Evaluation (SLiDE)
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma de Mallorca, Spain
%F lee-park-2026-quantification
%X Quantification is common in text, but it is underrepresented in AMR. Quantification also stresses the common conjunctive interpretation of AMR graphs, since universal quantification introduces scope-taking structure and variable binding that cannot be captured as a flat list of conjuncts. We propose an enriched AMR that supports quantificational meaning while keeping AMR’s graph backbone. At the predicate level, we add QuantML features, such as domain restriction, determinacy, distributivity, and involvement. At the discourse level, we add contextual constraints that encode scope and other discourse-sensitive conditions. The two levels follow the UMR architecture and are linked by shared identifiers. We map the enriched graphs to two-block logical forms: a minimal model of events and participants, plus a constraint block that relates them.
%R 10.63317/5nkejg7f845v
%U https://aclanthology.org/2026.slide-1.9/
%U https://doi.org/10.63317/5nkejg7f845v
%P 104-113

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Markdown (Informal)

[Quantification in Abstract Meaning Representation](https://aclanthology.org/2026.slide-1.9/) (Lee & Park, SLiDE 2026)

Quantification in Abstract Meaning Representation (Lee & Park, SLiDE 2026)

ACL

Kiyong Lee and Chongwon Park. 2026. Quantification in Abstract Meaning Representation. In Proceedings of the Workshop on Structured Linguistic Data and Evaluation (SLiDE), pages 104–113, Palma de Mallorca, Spain. ELRA Language Resources Association (ELRA).