---
license: cc-by-4.0
language:
- de
tags:
- Coreference Resolution
- NER
pretty_name: GerFuN
---

# 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.*](https://tuprints.ulb.tu-darmstadt.de/entities/publication/c248c5b4-40c3-488f-8673-c1a486dd2a05)

### Original Repository

https://github.com/aehrm/llm_literary_coref

### Citation

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

```bibtex
@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