---
title: "CorMet: A Computational, Corpus-Based — Mason 2004"
description: "CorMet addresses the automatic discovery of conventional metaphors."
authors: ["Zachary J. Mason"]
year: 2004
venue: "Computational Linguistics"
source: "https://aclanthology.org/J04-1002/"
doi: "10.1162/089120104773633376"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/mason-2004-cormet-computational-corpus-based-conventional/"
---
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# CorMet: A Computational, Corpus-Based Conventional Metaphor Extraction System

**Authors:** Zachary J. Mason · **Year:** 2004 · **Venue:** Computational Linguistics · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/J04-1002/) · [PDF](https://aclanthology.org/J04-1002.pdf) · [DOI 10.1162/089120104773633376](https://doi.org/10.1162/089120104773633376) · [OpenAlex](https://openalex.org/W2050797400)

**Citations:** 205 citations (OpenAlex, 2026-10-14) · [65](https://md.research.elamur.ai/free/en/papers/mason-2004-cormet-computational-corpus-based-conventional/cited-by/) in our library, of the 140884 papers whose bibliographies we read

## Summary
CorMet addresses the automatic discovery of conventional metaphors. These are systematic mappings that carry structure from a concrete source domain, such as liquids or warfare, into a target domain, such as money or medicine. Earlier computational metaphor models relied on small hand-built knowledge bases and covered only a few examples. CorMet uses only WordNet plus large web-mined corpora. For each user-specified domain, it builds a corpus from Google queries that combine random domain keywords. It then parses the pages, extracts verb case frames, and selects verbs that are unusually frequent compared with general English. Their domain-specific selectional preferences are learned with Resnik's algorithm followed by clustering. When a source-domain verb consistently takes a different concept class in the target domain, CorMet proposes an interconcept mapping. One example is pour, which takes funds in FINANCE but liquids in LAB. Clusters of such mappings indicate higher-level metaphors. Tested against a subset of the Master Metaphor List, the system recovers some listed metaphors with reasonable accuracy despite noisy components. This shows that a shallow corpus-based approach is viable, though not yet a practical NLP tool.

## Key points
- **Data and corpora:** Corpora are mined dynamically from the web. Each query returns up to 10,000 links, of which at most 3,000 documents are fetched. Across the 13 domains studied, about 75% of fetched documents were domain-relevant, based on a hand-checked sample of 100 per domain.
- **Pipeline:** After HTML and scripts are stripped from the pages, the text is syntactically analyzed using Sekine and Grishman's (1995) Apple Pie Parser. Case frames are extracted using syntactic templates.
- **Characteristic verbs:** Words are stemmed with the Porter stemmer. Each stem's frequency is compared with the BNC frequency list (Kilgarriff 2003), and the top 400 verb stems per domain are kept. Stems that score high in several domains, such as e-mail, are discarded.
- **Selectional preferences:** These are computed with Resnik's (1993) relative-entropy measures, selectional-preference strength and selectional association, over WordNet nodes. Preferences are compared via cosine similarity.
- **Knowledge sources and scope:** WordNet's noun hierarchy is the only knowledge base, and its verb information is deliberately ignored. The method works best for concrete, specific domains and common mappings. It does not detect every metaphor instance.

*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

- [Brandeis University](https://md.research.elamur.ai/free/en/universities/brandeis-university/) — University, Waltham, United States · 27 works · 4 999 citations

## Cite

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

```bibtex
@article{mason2004cormet,
  title = {{CorMet: A Computational, Corpus-Based Conventional Metaphor Extraction System}},
  author = {Mason, Zachary J.},
  journal = {Computational Linguistics},
  year = {2004},
  doi = {10.1162/089120104773633376},
  url = {https://doi.org/10.1162/089120104773633376}
}
```

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