---
title: "Metaphor Corpus Annotated for Source - Target — Shutova 2010"
description: "The paper addresses a gap in metaphor annotation. Most theories treat metaphor as one conceptual domain (target) being understood through another…"
authors: ["Ekaterina Shutova", "Simone Teufel"]
year: 2010
venue: "Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)"
source: "https://aclanthology.org/L10-1419/"
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/papers/shutova-2010-metaphor-corpus-annotated-source-target/"
---
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# Metaphor Corpus Annotated for Source - Target Domain Mappings

**Authors:** [Ekaterina Shutova](https://md.research.elamur.ai/free/authors/ekaterina-shutova/), [Simone Teufel](https://md.research.elamur.ai/free/authors/simone-teufel/) · **Year:** 2010 · **Venue:** Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/L10-1419/) · [PDF](https://aclanthology.org/L10-1419.pdf) · [OpenAlex](https://openalex.org/W56200336)

**Citations:** 98 citations (openalex-snapshot · 2026-10-14) · [66](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
The paper addresses a gap in metaphor annotation. Most theories treat metaphor as one conceptual domain (target) being understood through another (source), yet no systematic procedure existed for annotating these cross-domain mappings in text. Shutova and Teufel propose such a scheme for single-word metaphors expressed by verbs. They build on the Pragglejaz Group's MIP, reusing its notion of a "basic" sense: more concrete, bodily, precise and historically older. Annotators first decide whether each verb is literal or metaphorical. For metaphorical verbs, they then choose a source and a target category from predefined lists, or propose a new category if none fits. The lists draw on the Master Metaphor List and are extended with categories the authors found in their own annotated data. The procedure was tested with several annotators, and inter-annotator agreement was measured. The authors also ran a small BNC study showing that explicit linguistic cues are weak metaphor detectors. The resulting corpus was announced as publicly available and is meant to support linguistic, computational and cognitive research on conceptual metaphor.

## Key points
- The scope is limited to verb metaphors. Auxiliary, modal, aspectual (e.g. *begin*, *finish*) and light verbs (e.g. *take*, *make*) are excluded because they rarely act as metaphors.
- The category lists combine newly added categories with a subset taken from Lakoff et al.'s (1991) Master Metaphor List. Source examples include CONTAINER, JOURNEY and MACHINE/MECHANISM; target examples include TIME, IDEAS and RELATIONSHIP.
- On a held-out document set, the source list covered 100% of metaphorical expressions and the target list covered 76%.
- In a BNC study of Goatly's metaphor cues, 50 random sentences per cue were annotated (only 7 existed for *metaphorically speaking*).
  - Average precision was 0.40.
  - *metaphorically speaking* and *so to speak* reached 0.71.
  - *figurative* reached only 0.18.
- Some metaphors require chains of mappings. For example, *catch the contagion* involves IDEAS/VIEWS–INFECTION and INFECTION–PHYSICAL OBJECT, which makes it hard to fix the number of mappings per instance.

## Interesting ideas
- **Two-stage annotation.** A binary literal/metaphorical decision comes first, and a richer label (the domain mapping) is added only for positive cases. This keeps the easy decision separate from the harder one and suits any layered semantic annotation task.
- **Closed lists with an escape hatch.** Annotators pick from curated categories but may add their own when nothing fits. This balances consistency with coverage and reveals gaps in the label inventory.
- **Measuring label-set coverage on held-out data.** Checking how many held-out instances each list can describe (100% vs. 76%) is a cheap sanity check before full annotation. It works for any taxonomy-based scheme.
- **Operational criteria for "basic" senses.** Defining the basic sense as concrete, bodily, precise and older gives annotators testable rules instead of intuition. This is useful for annotating metaphor or sense extension in other languages, including Ukrainian.
- **Sampling-based precision checks for heuristics.** Annotating a small random sample per cue quickly showed that cue-based extraction is noisy. The same approach could vet any keyword-based data collection method before relying on it.

*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: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/)

## Cited by

Cited by

66 papers of our library cite it (of the 140673 whose bibliographies we read); 2 of them have a page here, 64 not yet.

- [Metaphor as a Medium for Emotion: An Empirical Study](https://md.research.elamur.ai/free/papers/mohammad-2016-metaphor-as-medium-emotion-empirical/)
- [Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models](https://md.research.elamur.ai/free/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)

## Cite

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

```bibtex
@inproceedings{shutova2010metaphor,
  title = {{Metaphor Corpus Annotated for Source - Target Domain Mappings}},
  author = {Shutova, Ekaterina and Teufel, Simone},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  doi = {10.63317/58pqcwstrund},
  url = {https://doi.org/10.63317/58pqcwstrund}
}
```

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