@inproceedings{rubehn-etal-2025-annotating,
    title = "Annotating and Inferring Compositional Structures in Numeral Systems Across Languages",
    author = "Rubehn, Arne  and
      Rzymski, Christoph  and
      Ciucci, Luca  and
      Bocklage, Katja  and
      Ku{\v{c}}erov{\'a}, Al{\v{z}}b{\v{e}}ta  and
      Snee, David  and
      Stephen, Abishek  and
      Dam, Kellen Parker Van  and
      List, Johann-Mattis",
    editor = "Hahn, Michael  and
      Rani, Priya  and
      Kumar, Ritesh  and
      Shcherbakov, Andreas  and
      Sorokin, Alexey  and
      Serikov, Oleg  and
      Cotterell, Ryan  and
      Vylomova, Ekaterina",
    booktitle = "Proceedings of the 7th Workshop on Research in Computational Linguistic Typology and Multilingual NLP",
    month = aug,
    year = "2025",
    address = "Vinenna. Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.sigtyp-1.4/",
    pages = "29--42",
    ISBN = "979-8-89176-281-7",
    abstract = "Numeral systems across the world{'}s languages vary in fascinating ways, both regarding their synchronic structure and the diachronic processes that determined how they evolved in their current shape. For a proper comparison of numeral systems across different languages, however, it is important to code them in a standardized form that allows for the comparison of basic properties. Here, we present a simple but effective coding scheme for numeral annotation, along with a workflow that helps to code numeral systems in a computer-assisted manner, providing sample data for numerals from 1 to 40 in 25 typologically diverse languages. We perform a thorough analysis of the sample, focusing on the systematic comparison between the underlying and the surface morphological structure. We further experiment with automated models for morpheme segmentation, where we find allomorphy as the major reason for segmentation errors. Finally, we show that subword tokenization algorithms are not viable for discovering morphemes in low-resource scenarios."
}