@inproceedings{buljan-etal-2024-argument,
    title = "Argument Sharing in Meaning Representation Parsing",
    author = "Buljan, Maja  and
      Oepen, Stephan  and
      {\O}vrelid, Lilja",
    editor = "Bonial, Claire  and
      Bonn, Julia  and
      Hwang, Jena D.",
    booktitle = "Proceedings of the Fifth International Workshop on Designing Meaning Representations @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.dmr-1.9",
    pages = "77--87",
    abstract = "We present a contrastive study of argument sharing across three graph-based meaning representation frameworks, where semantically shared arguments manifest as reentrant graph nodes. For a state-of-the-art graph parser, we observe how parser performance {--} in terms of output quality {--} covaries with overall graph complexity, on the one hand, and presence of different types of reentrancies, on the other hand. We identify common linguistic phenomena that give rise to shared arguments, and therefore node reentrancies, through a small-case and partially automated annotation study and parallel error anaylsis of actual parser outputs. Our results provide new insights into the distribution of different types of reentrancies in meaning representation graphs for three distinct frameworks, as well as on the effects that these structures have on parser performance, thus suggesting both novel cross-framework generalisations as well as avenues for focussed parser development.",
}

We present a contrastive study of argument sharing across three graph-based meaning representation frameworks, where semantically shared arguments manifest as reentrant graph nodes. For a state-of-the-art graph parser, we observe how parser performance {--} in terms of output quality {--} covaries with overall graph complexity, on the one hand, and presence of different types of reentrancies, on the other hand. We identify common linguistic phenomena that give rise to shared arguments, and therefore node reentrancies, through a small-case and partially automated annotation study and parallel error anaylsis of actual parser outputs. Our results provide new insights into the distribution of different types of reentrancies in meaning representation graphs for three distinct frameworks, as well as on the effects that these structures have on parser performance, thus suggesting both novel cross-framework generalisations as well as avenues for focussed parser development.
Buljan, Maja Oepen, Stephan {\O}vrelid, Lilja
Argument Sharing in Meaning Representation Parsing