COLING 2024main2 citations

Croatian Idioms Integration: Enhancing the LIdioms Multilingual Linked Idioms Dataset

Ivana Filipović Petrović, Miguel López Otal, Slobodan Beliga

Abstract

Idioms, also referred to as phraseological units in some language terminologies, are a subset within the broader category of multi-word expressions. However, there is a lack of representation of idioms in Croatian, a low-resourced language, in the Linguistic Linked Open Data cloud (LLOD). To address this gap, we propose an extension of an existing RDF-based multilingual representation of idioms, referred to as the LIdioms dataset, which currently includes idioms from English, German, Italian, Portuguese, and Russian. This paper expands the existing resource by incorporating 1,042 Croatian idioms in an Ontolex Lemon format. In addition, to foster translation initiatives and facilitate intercultural exchange, these added Croatian idioms have also been linked to other idioms of the LIdioms dataset, with which they share similar meanings despite their differences in the expression aspect. This addition enriches the knowledge base of the LLOD community with a new language resource that includes Croatian idioms.

BibTeX
@inproceedings{filipovic-petrovic-etal-2024-croatian,
    title = "{C}roatian Idioms Integration: Enhancing the {LI}dioms Multilingual Linked Idioms Dataset",
    author = "Filipovi{\'c} Petrovi{\'c}, Ivana  and
      L{\'o}pez Otal, Miguel  and
      Beliga, Slobodan",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.366/",
    pages = "4106--4112"
}
Croatian Idioms Integration: Enhancing the LIdioms Multilingual Linked Idioms Dataset · COLING 2024