@inproceedings{jablotschkin-etal-2026-errors,
    title = "Errors in coreference resolution in {G}erman: Effects of modality, simplification and heterogeneous training data",
    author = "Jablotschkin, Sarah  and
      Lapshinova-Koltunski, Ekaterina  and
      Zinsmeister, Heike",
    editor = "Braud, Chlo{\'e}  and
      Hardmeier, Christian  and
      Ogrodniczuk, Maciej  and
      Loaiciga, Sharid  and
      Zeldes, Amir  and
      Nov{\'a}k, Michal  and
      Li, Chuyuan  and
      Strube, Michael  and
      Li, Junyi Jessy",
    booktitle = "Proceedings of the 2nd Joint Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences and Computational Models of Reference, Anaphora and Coreference ({CODI}-{CRAC} 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.codi-1.14/",
    pages = "109--119",
    ISBN = "979-8-89176-400-2",
    abstract = "Errors in automatic coreference resolution can be traced back to errors in mention detection and coreference linking. In this paper, we analyse the errors in mention detection produced by the coreference resolver CorPipe (Straka 2023). In particular, we evaluate the performance on different variants of German (written, spoken, original, and simplified). We discuss the errors against the background of the fact that the tool was trained on a combination of different coreference corpora, including two German datasets with partially conflicting annotation guidelines. The results indicate that simplification has a significant effect on mention detection independent of the modality."
}