A Structured Syntax-Semantics Interface for English-AMR Alignment

Ida Szubert, Adam Lopez, Schneider Nathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Abstract Meaning Representation (AMR) annotations are often assumed to closely mirror dependency syntax, but AMR explicitly does not require this, and the assumption has never been tested. To test it, we devise an expressive framework to align AMR graphs to dependency graphs, which we use to annotate 200 AMRs. Our annotation explains how 97% of AMR edges are evoked by words or syntax. Previously existing AMR alignment frameworks did not allow for mapping AMR onto syntax, and as a consequence they explained at most 23%. While we find that there are indeed many cases where AMR annotations closely mirror syntax, there are also pervasive differences. We use our annotations to test a baseline AMR-to-syntax aligner, finding that this task is more difficult than AMRto-string alignment; and to pinpoint errors in an AMR parser. We make our data and code freely available for further research on AMR parsing and generation, and the relationship of AMR to syntax.
Original languageEnglish
Title of host publicationThe 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Place of PublicationNew Orleans, Louisiana
PublisherAssociation for Computational Linguistics
Pages1169-1180
Number of pages12
DOIs
Publication statusPublished - 1 Jun 2018
Event16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Hyatt Regency New Orleans Hotel, New Orleans, United States
Duration: 1 Jun 20186 Jun 2018
http://naacl2018.org/

Conference

Conference16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Abbreviated titleNAACL HLT 2018
Country/TerritoryUnited States
CityNew Orleans
Period1/06/186/06/18
Internet address

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