---
title: "A Novel Dataset and Three Ways to Approach Automatic Metaphor Detection in German — Reimann 2026"
description: "The authors build a new German corpus from the Christian forum jesus.de, sampling threads that mention the word Metapher . 37 references."
authors: ["Sebastian Reimann", "Tatjana Scheffler"]
year: 2026
venue: "Proceedings of Learning Non-Literal Expressions with Small Data @ LREC 2026"
source: "https://aclanthology.org/2026.nonliteral-1.10/"
doi: "10.63317/5n9kbko8vezs"
licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/reimann-2026-novel-dataset-three-ways-approach/"
---
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# A Novel Dataset and Three Ways to Approach Automatic Metaphor Detection in German Religious Online Forums

**Authors:** Sebastian Reimann and [Tatjana Scheffler](https://md.research.elamur.ai/free/en/authors/tatjana-scheffler/) · **Year:** 2026 · **Venue:** Proceedings of Learning Non-Literal Expressions with Small Data @ LREC 2026 · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.nonliteral-1.10/) · [PDF](https://aclanthology.org/2026.nonliteral-1.10.pdf) · [DOI 10.63317/5n9kbko8vezs](https://doi.org/10.63317/5n9kbko8vezs) · [OpenAlex](https://openalex.org/W7166571484)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Most work on automatic metaphor detection targets English and a narrow set of genres. That leaves German and religious discourse poorly covered, even though metaphor is central to how believers talk about God and the transcendent. The authors build a new German corpus from the Christian forum jesus.de, sampling threads that mention the word *Metapher*. They annotate nouns, verbs, adjectives and adverbs using the German adaptation of MIPVU.

They then test three ways of coping with scarce training data:
- cross-lingual transfer, fine-tuning multilingual encoder-only models on English Christian Reddit posts;
- cross-genre transfer from the much larger VUA corpus;
- LLM prompting that walks the model through the MIPVU decision steps.

Fine-tuned encoders outperform prompting, and different contextual-embedding architectures behave in clearly different ways. A small training set from a matching genre, even in another language, can be preferable to a large set from unrelated genres. Cross-lingual transfer mainly works when a conceptual mapping is shared by both languages. The released dataset is presented as the largest publicly available German metaphor resource, which helps fill a gap for German NLP and for computational religion studies.

## Key points
- **Dataset:** German posts from jesus.de, annotated by four native German annotators with backgrounds in computational linguistics, religious sciences and philosophy/English linguistics.
- **Annotation scheme:** MIPVU with the German variant by Herrmann et al. (2019), using Duden and DWDS as reference dictionaries.
  - Both indirect and direct MRWs are covered.
  - Lexicalized phrases such as *es gibt* are treated synchronically.
- **English training sources:**
  - The Christian subreddit data of Reimann and Scheffler (2024), under CC-BY-4.0.
  - The VUA version from the 2020 Metaphor Detection Shared Task, under CC BY-SA 3.0.
  - Both are annotated for content words only.
- **Prompting setup:** a three-stage pipeline mirroring MIPVU steps 3a–3c.
  - The model gives the contextual meaning, then a more basic meaning, then judges whether the two are similar.
  - Parallel English and German prompts are used; the worked example is *journey* in English and *Weg* in German.
- **Contribution and availability:** the authors describe this as the first study to directly compare cross-lingual transfer, cross-genre transfer and prompting for metaphor detection. The data is released on GitHub (SFB-1475, C04-Cross-Lingual-MD).

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/)

Topics: [🧷 Idioms & multiword expressions](https://md.research.elamur.ai/free/en/topics/multiword-expressions/)

## Institutions

- [Ruhr University Bochum](https://md.research.elamur.ai/free/en/universities/ruhr-university-bochum/) — University, Bochum, Germany · 19 works · 1,147 citations

## Cite

Cite as: Sebastian Reimann and Tatjana Scheffler. 2026. A Novel Dataset and Three Ways to Approach Automatic Metaphor Detection in German Religious Online Forums. Proceedings of Learning Non-Literal Expressions with Small Data @ LREC 2026.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{reimann2026novel,
  title = {{A Novel Dataset and Three Ways to Approach Automatic Metaphor Detection in German Religious Online Forums}},
  author = {Sebastian Reimann and Tatjana Scheffler},
  booktitle = {Proceedings of Learning Non-Literal Expressions with Small Data @ LREC 2026},
  year = {2026},
  doi = {10.63317/5n9kbko8vezs},
  url = {https://doi.org/10.63317/5n9kbko8vezs}
}
```

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