@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://aclanthology.org/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."
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<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.</abstract>
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%0 Conference Proceedings
%T Errors in coreference resolution in German: Effects of modality, simplification and heterogeneous training data
%A Jablotschkin, Sarah
%A Lapshinova-Koltunski, Ekaterina
%A Zinsmeister, Heike
%Y Braud, Chloé
%Y Hardmeier, Christian
%Y Ogrodniczuk, Maciej
%Y Loaiciga, Sharid
%Y Zeldes, Amir
%Y Novák, Michal
%Y Li, Chuyuan
%Y Strube, Michael
%Y Li, Junyi Jessy
%S 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)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-400-2
%F jablotschkin-etal-2026-errors
%X 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.
%U https://aclanthology.org/2026.codi-1.14/
%P 109-119
Markdown (Informal)
[Errors in coreference resolution in German: Effects of modality, simplification and heterogeneous training data](https://aclanthology.org/2026.codi-1.14/) (Jablotschkin et al., CODI-CRAC 2026)
ACL