All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Abstract meaning representation of Turkish

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A2PTZLRHA" target="_blank" >RIV/00216208:11320/22:2PTZLRHA - isvavai.cz</a>

  • Result on the web

    <a href="https://www.cambridge.org/core/journals/natural-language-engineering/article/abstract-meaning-representation-of-turkish/35E839E5AF1F7B9F6BF16275A44BB71D" target="_blank" >https://www.cambridge.org/core/journals/natural-language-engineering/article/abstract-meaning-representation-of-turkish/35E839E5AF1F7B9F6BF16275A44BB71D</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1017/S1351324922000183" target="_blank" >10.1017/S1351324922000183</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Abstract meaning representation of Turkish

  • Original language description

    Abstract 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Natural Language Engineering

  • ISSN

    1351-3249

  • e-ISSN

    1469-8110

  • Volume of the periodical

  • Issue of the periodical within the volume

    2022-4-28

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    30

  • Pages from-to

    1-30

  • UT code for WoS article

    000792144500001

  • EID of the result in the Scopus database

    2-s2.0-85129562470