@inproceedings{sitter-etal-2025-annotating,
    title = "Annotating Spatial Descriptions in Literary and Non-Literary Text",
    author = "Sitter, Emilie  and
      Momen, Omar  and
      Steig, Florian  and
      Herrmann, J. Berenike  and
      Zarrie{\ss}, Sina",
    editor = "Peng, Siyao  and
      Rehbein, Ines",
    booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.law-1.26/",
    doi = "10.18653/v1/2025.law-1.26",
    pages = "308--325",
    ISBN = "979-8-89176-262-6",
    abstract = "Descriptions are a central component of literary texts, yet their systematic identification remains a challenge. This work suggests an approach to identifying sentences describing spatial conditions in literary text. It was developed iteratively on German literary text and extended to non-literary text to evaluate its applicability across textual domains. To assess the robustness of the method, we involved both humans and a selection of state-of-the-art Large Language Models (LLMs) in annotating a collection of sentences regarding their descriptiveness and spatiality. We compare the annotations across human annotators and between humans and LLMs. The main contributions of this paper are: (1) a set of annotation guidelines for identifying spatial descriptions in literary texts, (2) a curated dataset of almost 4,700 annotated sentences of which around 500 are spatial descriptions, produced through in-depth discussion and consensus among annotators, and (3) a pilot study of automating the task of spatial description annotation of German texts. We publish the codes and all human and LLM annotations for the public to be used for research purposes only."
}