@inproceedings{ishizuki-etal-2024-drop,
    title = "To Drop or Not to Drop? Predicting Argument Ellipsis Judgments: A Case Study in {J}apanese",
    author = "Ishizuki, Yukiko  and
      Kuribayashi, Tatsuki  and
      Matsubayashi, Yuichiroh  and
      Sasano, Ryohei  and
      Inui, Kentaro",
    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.1408",
    pages = "16198--16210",
    abstract = "Speakers sometimes omit certain arguments of a predicate in a sentence; such omission is especially frequent in pro-drop languages. This study addresses a question about ellipsis{---}what can explain the native speakers{'} ellipsis decisions?{---}motivated by the interest in human discourse processing and writing assistance for this choice. To this end, we first collect large-scale human annotations of whether and why a particular argument should be omitted across over 2,000 data points in the balanced corpus of Japanese, a prototypical pro-drop language. The data indicate that native speakers overall share common criteria for such judgments and further clarify their quantitative characteristics, e.g., the distribution of related linguistic factors in the balanced corpus. Furthermore, the performance of the language model{--}based argument ellipsis judgment model is examined, and the gap between the systems{'} prediction and human judgments in specific linguistic aspects is revealed. We hope our fundamental resource encourages further studies on natural human ellipsis judgment.",
}

Speakers sometimes omit certain arguments of a predicate in a sentence; such omission is especially frequent in pro-drop languages. This study addresses a question about ellipsis{---}what can explain the native speakers{'} ellipsis decisions?{---}motivated by the interest in human discourse processing and writing assistance for this choice. To this end, we first collect large-scale human annotations of whether and why a particular argument should be omitted across over 2,000 data points in the balanced corpus of Japanese, a prototypical pro-drop language. The data indicate that native speakers overall share common criteria for such judgments and further clarify their quantitative characteristics, e.g., the distribution of related linguistic factors in the balanced corpus. Furthermore, the performance of the language model{--}based argument ellipsis judgment model is examined, and the gap between the systems{'} prediction and human judgments in specific linguistic aspects is revealed. We hope our fundamental resource encourages further studies on natural human ellipsis judgment.
Ishizuki, Yukiko Kuribayashi, Tatsuki Matsubayashi, Yuichiroh Sasano, Ryohei Inui, Kentaro
To Drop or Not to Drop? Predicting Argument Ellipsis Judgments: A Case Study in Japanese