@inproceedings{gamba-etal-2024-universal,
    title = "Universal Feature-based Morphological Trees",
    author = "Gamba, Federica  and
      Stephen, Abishek  and
      {\v{Z}}abokrtsk{\'y}, Zden{\v{e}}k",
    editor = {Bhatia, Archna  and
      Bouma, Gosse  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Evang, Kilian  and
      Garcia, Marcos  and
      Giouli, Voula  and
      Han, Lifeng  and
      Nivre, Joakim  and
      Rademaker, Alexandre},
    booktitle = "Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.mwe-1.17",
    pages = "125--137",
    abstract = "The paper proposes a novel data representation inspired by Universal Dependencies (UD) syntactic trees, which are extended to capture the internal morphological structure of word forms. As a result, morphological segmentation is incorporated within the UD representation of syntactic dependencies. To derive the proposed data structure we leverage existing annotation of UD treebanks as well as available resources for segmentation, and we select 10 languages to work with in the presented case study. Additionally, statistical analysis reveals a robust correlation between morphs and sets of morphological features of words. We thus align the morphs to the observed feature inventories capturing the morphological meaning of morphs. Through the beneficial exploitation of cross-lingual correspondence of morphs, the proposed syntactic representation based on morphological segmentation proves to enhance the comparability of sentence structures across languages.",
}

The paper proposes a novel data representation inspired by Universal Dependencies (UD) syntactic trees, which are extended to capture the internal morphological structure of word forms. As a result, morphological segmentation is incorporated within the UD representation of syntactic dependencies. To derive the proposed data structure we leverage existing annotation of UD treebanks as well as available resources for segmentation, and we select 10 languages to work with in the presented case study. Additionally, statistical analysis reveals a robust correlation between morphs and sets of morphological features of words. We thus align the morphs to the observed feature inventories capturing the morphological meaning of morphs. Through the beneficial exploitation of cross-lingual correspondence of morphs, the proposed syntactic representation based on morphological segmentation proves to enhance the comparability of sentence structures across languages.
Gamba, Federica Stephen, Abishek {\v{Z}}abokrtsk{\'y}, Zden{\v{e}}k
Universal Feature-based Morphological Trees