rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Neural morphological generators for Hungarian
  name:
    name part: Laki László János
    role:
      role term: creator
  name:
    name part: Ligeti-Nagy Noémi
    role:
      role term: aut
  name:
    name part: Vadász Noémi
    role:
      role term: aut
  name:
    name part: Yang Zijian Győző
    role:
      role term: aut
  name:
    name part: Magyar számítógépes nyelvészeti konferencia (19.) Szeged 2023. január 26-27.
  type of resource: text
  genre: conference publication
  origin info:
    place:
      place term: hu
    date issued: 2023
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: elektronikus dokumentum
    extent: 331-340
  abstract: Here we present a set of morphological generators for Hungarian that generate surface forms from emMorph and Universal Dependencies (UD) morphological tags with high accuracy. We experimented with two approaches: first, neural machine translation models were trained based on the morphological analysis as the source format and the corresponding surface form as the target format. Second, we tackled the problem as a text generation task, where the morphological analysis is followed by the correct word form. The corpus we used is a normalised version of Webcorpus 2.0 (Nemeskey, 2020). Marian MT proved to produce the best results, thus we evaluated its output manually on NerKor (Simon and Vadász, 2021). Our analysis shows that the generator achieves a high accuracy of 96.27% in the case of emMorph and 94.94% in the case of UD. After manual evaluation, we counted a more concise accuracy, which is 99.43% (emMorph) and 98.69% (UD). This model may be used for several NLP tasks, such as anonymisation and terminology translation.
  note: Laki László János
  subject:
    topic: Természettudományok
  subject:
    topic: Számítás- és információtudomány
  related item:
    title info:
      title: Magyar Számítógépes Nyelvészeti Konferencia 19
  identifier: 978-963-306-912-7
  identifier: http://acta.bibl.u-szeged.hu/78423/1/msznykonf_019_331-340..pdf
  record info:
    record content source: SZTE Egyetemi Kiadványok Repozitórium
    record creation date: 230316
    record change date: 20230316095836.0
    record identifier: acta78423
    language of cataloging:
      language term: hun