Abstract meaning representation of Turkish

Elif Oral, Ali Acar, Gülşen Eryiğit*

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2 Atıf (Scopus)

Özet

meaning representation (AMR) is a graph-based sentence-level meaning representation that has become highly popular in recent years. AMR is a knowledge-based meaning representation heavily relying on frame semantics for linking predicate frames and entity knowledge bases such as DBpedia for linking named entity concepts. Although it is originally designed for English, its adaptation to non-English languages is possible by defining language-specific divergences and representations. This article introduces the first AMR representation framework for Turkish, which poses diverse challenges for AMR due to its typological differences compared to English; agglutinative, free constituent order, morphologically highly rich resulting in fewer word surface forms in sentences. The introduced solutions to these peculiarities are expected to guide the studies for other similar languages and speed up the construction of a cross-lingual universal AMR framework. Besides this main contribution, the article also presents the construction of the first AMR corpus of 700 sentences, the first AMR parser (i.e., a tree-to-graph rule-based AMR parser) used for semi-automatic annotation, and the evaluation of the introduced resources for Turkish.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)171-200
Sayfa sayısı30
DergiNatural Language Engineering
Hacim30
Basın numarası1
DOI'lar
Yayın durumuYayınlandı - 28 Oca 2024

Bibliyografik not

Publisher Copyright:
© The Author(s), 2022.

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