Datasets:

lattice-nlp
/

GerFuN

file_name stringclasses 5 values	language stringclasses 1 value	text stringclasses 5 values	stanza_tokens int64 25k 200k	mentions listlengths 4.06k 23.6k	sentence_spans listlengths 1.38k 9.33k
Fischer_Gustav	de	"Caroline Auguste Fischer Gustavs Verirrungen Ein Roman [ Vorbemerkung ] Man erzählt uns oft , was (...TRUNCATED)	24,970	[{"onset":72,"offset":75,"COREF":"generic_0001","type":"PER","entity_id":"generic_0122","gender":"u"(...TRUNCATED)	[[0,315],[315,462],[462,475],[475,568],[568,664],[664,752],[752,814],[814,906],[906,970],[970,1048],(...TRUNCATED)
Goethe_Wahlverwandtschaften	de	"Johann Wolfgang Goethe Die Wahlverwandtschaften Ein Roman Erster Teil\n\nErstes Kapitel\n\nEduard (...TRUNCATED)	93,875	[{"onset":87,"offset":93,"COREF":"Eduard","type":"PER","entity_id":"entity_0001","gender":"m","speci(...TRUNCATED)	[[0,71],[71,87],[87,307],[307,523],[523,619],[619,677],[677,777],[777,839],[839,1016],[1016,1119],[1(...TRUNCATED)
Heimburg_Trudchen	de	"1.\n\n» Wahrhaftig , Franz , an deiner Stelle wüßte ich nicht , ob ich lachen oder weinen sollte(...TRUNCATED)	65,058	[{"onset":6,"offset":16,"COREF":"Richard_Weishaupt","type":"PER","entity_id":"entity_0002","gender":(...TRUNCATED)	[[0,4],[4,97],[97,240],[240,278],[278,348],[348,689],[689,859],[859,978],[978,1205],[1205,2087],[208(...TRUNCATED)
Kürnberger_Amerika	de	"Erstes Buch .\n\nErstes Kapitel .\n\n„ Amerika ! Welcher Name hat einen Inhalt gleich diesem Name(...TRUNCATED)	199,958	[{"onset":97,"offset":100,"COREF":"Im_materiellen_verhafteter_Mensch","type":"PER","entity_id":"gene(...TRUNCATED)	[[0,15],[15,33],[33,45],[45,97],[97,192],[192,265],[265,356],[356,459],[459,595],[595,662],[662,717](...TRUNCATED)
Wolff_Wildfangrecht	de	"Julius Wolff Das Wildfangrecht Eine pfälzische Geschichte\n\nErstes Kapitel .\n\nAn einem warmen S(...TRUNCATED)	79,148	[{"onset":144,"offset":148,"COREF":"Christoph_Armbruster","type":"PER","entity_id":"entity_0001","ge(...TRUNCATED)	[[0,59],[59,77],[77,302],[302,431],[431,589],[589,773],[773,942],[942,1229],[1229,1678],[1678,1890],(...TRUNCATED)

GerFuN

Dataset Summary

This repository provides a standardized and reformatted version of the original GerFuN coreference resolution dataset.

The purpose of this formatting is to provide a unified document structure across multiple coreference datasets in order to simplify:

cross-dataset comparison,
multilingual experimentation,
benchmarking of coreference resolution systems,
interoperability between NLP pipelines,
and reproducible evaluation settings.

This repository does not introduce new annotations or modify the original coreference annotations. It only restructures the original dataset into a shared schema used across our benchmarking framework.

Original Dataset

This formatted version is derived from the dataset introduced in:

Agnes Hilger and Anton Ehrmanntraut. 2026. Coreference Resolution for Full German Novels using Large Language Models.

Original Repository

https://github.com/aehrm/llm_literary_coref

Citation

If you use this dataset, please cite the original work:

@misc{Hilger_Ehrmanntraut_2026,
    title={Coreference Resolution for Full German Novels using Large Language Models},
    author={Hilger, Agnes and Ehrmanntraut, Anton},
    volume={5},
    url={https://tuprints.ulb.tu-darmstadt.de/handle/tuda/15404},
    DOI={https://doi.org/10.26083/tuda-7983},
    year={2026}
}

Statistics

Statistic	Value
Language	de
Documents	5
Sentences	21,266
Tokens	463,009
Characters	2,575,101
Mentions	61,307
Entities	8,135

Dataset Structure

Each document contains:

file_name
language
text
stanza_tokens
mentions
sentence_spans

Mentions

Each mention contains the following fields and additional fields per-dataset:

onset
offset
COREF

Example

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Number of rows:

Total file size:

2.83 MB