Modeling Quantification and Scope in Abstract Meaning Representations
James D. Pustejovsky, Kenneth Lai, Nianwen Xue · 2019
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.