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Abstract Meaning Representation (AMR)[1][2] is a semantic representation language. AMR graphs are rooted, labeled, directed, acyclic graphs (DAGs), comprising whole sentences. They are intended to abstract away from syntactic representations, in the sense that sentences which are similar in meaning should be assigned the same AMR, even if they are not identically worded. By nature, the AMR language is biased towards English – it is not meant to function as an international auxiliary language.
Abstract Meaning Representations have originally been introduced by Langkilde and Knight (1998)[3] as a derivation from the Penman Sentence Plan Language,[4] they are thus continuing a long tradition in Natural Language Generation and this has been their original domain of application. AMRs have re-gained attention since Banarescu et al. (2013),[1] in particular, this includes the extension to novel tasks such as machine translation and natural language understanding. The modern (post-2010) AMR format preserves the syntax and many syntactic conceptions of the original AMR format but has been thoroughly revised to better align with PropBank. Moreover, AMR has been extended with formal conventions for metadata and conventions for entity linking (here, linking with Wikipedia entries).
Existing AMR technology includes tools and libraries for parsing,[5] visualization,[6] and surface generation[7] as well as a considerable number of publicly available data sets. Many of these resources are collected at the AMR homepage[8] at ISI/USC where AMR technology has been originally developed.
^ abBanarescu, Laura; Bonial, Claire; Cai, Shu; Georgescu, Madalina; Griffitt, Kira; Hermjakob, Ulf; Knight, Kevin; Koehn, Philipp; Palmer, Martha; Schneider, Nathan (2013). Abstract Meaning Representation for Sembanking(PDF). Sofia, Bulgaria: Association for Computational Linguistics. pp. 178–186. Retrieved 28 June 2019.
^"Abstract Meaning Representation (AMR)".
^Langkilde, Irene and Knight, Kevin (1998), Generation that Exploits Corpus-Based Statistical Knowledge, In COLING 1998 Volume 1: The 17th International Conference on Computational Linguistics
^Kasper, Robert T. (1989). "A flexible interface for linking applications to Penman's sentence generator". Proceedings of the Workshop on Speech and Natural Language - HLT '89. Philadelphia, Pennsylvania: Association for Computational Linguistics: 153–158. doi:10.3115/100964.100979.
^Montréal, RALI, Université de (2021-06-25), GoPhi : an AMR to ENGLISH VERBALIZER, retrieved 2022-03-16{{citation}}: CS1 maint: multiple names: authors list (link)
^"Abstract Meaning Representation (AMR)". amr.isi.edu. Retrieved 2022-03-16.
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