Coreference Resolution for Full German Novels using Large Language Models

The paper introduces the GerFuN dataset, consisting of five German-language novels fully annotated for character coreference, comprising a total of 450,000 tokens. Using a semi-manual pipeline, we first pre-annotated the novels using a LLM, and then manually corrected the annotations in the INCEpTION tool. The annotation guidelines, which build on existing approaches but are made more explicit and refined, are presented in the paper and released alongside the dataset. Finally, we evaluate LLMs on GerFuN, which surpass previous pipelines and exhibit near-human accuracy on prototypical cases of particular interest to literary studies.

Authors

Publication Details

Journal
Open MIND
Published
2026-04-21
DOI
https://doi.org/10.26083/tuda-7983
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Coreference Resolution for Full German Novels using Large Language Models

Agnes Hilger, Anton Ehrmanntraut
Open MIND
Authorship Attribution and Profiling
article

Coreference Resolution for Full German Novels using Large Language Models

Agnes Hilger, Anton Ehrmanntraut
article en

Abstract

The paper introduces the GerFuN dataset, consisting of five German-language novels fully annotated for character coreference, comprising a total of 450,000 tokens. Using a semi-manual pipeline, we first pre-annotated the novels using a LLM, and then manually corrected the annotations in the INCEpTION tool. The annotation guidelines, which build on existing approaches but are made more explicit and refined, are presented in the paper and released alongside the dataset. Finally, we evaluate LLMs on GerFuN, which surpass previous pipelines and exhibit near-human accuracy on prototypical cases of particular interest to literary studies.

Open MIND
Quality Education
Openalex Percentile: Top 6%
Authorship Attribution and Profiling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Coreference Resolution for Full German Novels using Large Language Models — Agnes Hilger, Anton Ehrmanntraut · Open MIND (2026) | TGRS Research Map | TGRS