How much of UCCA can be predicted from AMR? - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2022

How much of UCCA can be predicted from AMR?

Siyana Pavlova
Maxime Amblard
Bruno Guillaume

Abstract

In this paper, we consider two of the currently popular semantic frameworks: Abstract Meaning Representation (AMR)a more abstract framework, and Universal Conceptual Cognitive Annotation (UCCA)-an anchored framework. We use a corpus-based approach to build two graph rewriting systems, a deterministic and a non-deterministic one, from the former to the latter framework. We present their evaluation and a number of ambiguities that we discovered while building our rules. Finally, we provide a discussion and some future work directions in relation to comparing semantic frameworks of different flavors.
Fichier principal
Vignette du fichier
main.pdf (960.02 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03724129 , version 1 (22-07-2022)

Identifiers

Cite

Siyana Pavlova, Maxime Amblard, Bruno Guillaume. How much of UCCA can be predicted from AMR?. ISA 2022 : 18th Joint ACL - ISO Workshop on Interoperable Semantic Annotation, Jun 2022, Marseille, France. ⟨hal-03724129⟩
43 View
37 Download

Altmetric

Share

Gmail Facebook X LinkedIn More