Modeling Quantification and Scope in Abstract Meaning Representations

WS 2019  ·  James Pustejovsky, Ken Lai, Nianwen Xue ·

In this paper, we propose an extension to Abstract Meaning Representations (AMRs) to encode scope information of quantifiers and negation, in a way that overcomes the semantic gaps of the schema while maintaining its cognitive simplicity. Specifically, we address three phenomena not previously part of the AMR specification: quantification, negation (generally), and modality. The resulting representation, which we call {``}Uniform Meaning Representation{''} (UMR), adopts the predicative core of AMR and embeds it under a {``}scope{''} graph when appropriate. UMR representations differ from other treatments of quantification and modal scope phenomena in two ways: (a) they are more transparent; and (b) they specify default scope when possible.{`}

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