@inproceedings{edlin-reiss-2023-identifying,
    title = "Identifying Visual Depictions of Animate Entities in Narrative Comics: An Annotation Study",
    author = "Edlin, Lauren  and
      Reiss, Joshua",
    editor = "Akoury, Nader  and
      Clark, Elizabeth  and
      Iyyer, Mohit  and
      Chaturvedi, Snigdha  and
      Brahman, Faeze  and
      Chandu, Khyathi",
    booktitle = "Proceedings of the 5th Workshop on Narrative Understanding",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.wnu-1.14",
    doi = "10.18653/v1/2023.wnu-1.14",
    pages = "82--91",
    abstract = "Animate entities in narrative comics stories are expressed through a number of visual representations across panels. Identifying these entities is necessary for recognizing characters and analysing narrative affordances unique to comics, and integrating these with linguistic reference annotation, however an annotation process for animate entity identification has not received adequate attention. This research explores methods for identifying animate entities visually in comics using annotation experiments. Two rounds of inter-annotator agreement experiments are run: the first asks annotators to outline areas on comic pages using a Polygon segmentation tool, and the second prompts annotators to assign each outlined entity{'}s animacy type to derive a quantitative measure of agreement. The first experiment results show that Polygon-based outlines successfully produce a qualitative measure of agreement; the second experiment supports that animacy status is best conceptualised as a graded, rather than binary, concept.",
}

Animate entities in narrative comics stories are expressed through a number of visual representations across panels. Identifying these entities is necessary for recognizing characters and analysing narrative affordances unique to comics, and integrating these with linguistic reference annotation, however an annotation process for animate entity identification has not received adequate attention. This research explores methods for identifying animate entities visually in comics using annotation experiments. Two rounds of inter-annotator agreement experiments are run: the first asks annotators to outline areas on comic pages using a Polygon segmentation tool, and the second prompts annotators to assign each outlined entity{'}s animacy type to derive a quantitative measure of agreement. The first experiment results show that Polygon-based outlines successfully produce a qualitative measure of agreement; the second experiment supports that animacy status is best conceptualised as a graded, rather than binary, concept.
Edlin, Lauren Reiss, Joshua
Identifying Visual Depictions of Animate Entities in Narrative Comics: An Annotation Study