---
title: "Introducing PerMet 1.0 — Miri 2026"
description: "Persian has had no large, publicly available metaphor-annotated resource that covers several types of text."
authors: ["Mohammad Saeid Miri"]
year: 2026
venue: "Proceedings of the Fifteenth Language Resources and Evaluation Conference"
source: "https://aclanthology.org/2026.lrec-1.379/"
doi: "10.63317/26xmdq7f998f"
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/miri-2026-introducing-permet-1-0-metaphor/"
---
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# Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian

**Authors:** Mohammad Saeid Miri · **Year:** 2026 · **Venue:** Proceedings of the Fifteenth Language Resources and Evaluation Conference · **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.lrec-1.379/) · [PDF](https://aclanthology.org/2026.lrec-1.379.pdf) · [DOI 10.63317/26xmdq7f998f](https://doi.org/10.63317/26xmdq7f998f) · [OpenAlex](https://openalex.org/W7160118270)

**Citations:** 0 citations (openalex-snapshot · 2026-10-14)

## Summary
Persian has had no large, publicly available metaphor-annotated resource that covers several types of text. The only open dataset, the Persian MIPVU Corpus (PMC), contains about 30,000 tokens, all from news. This paper presents PerMet 1.0, a manually annotated Persian corpus of 120,343 tokens (99,079 lexical units). It covers five registers: academic writing, news, fiction, social media and spoken language.

The texts were gathered in four ways:
- sampling existing corpora,
- scraping web pages,
- running OCR on scanned books,
- transcribing audio recordings.

Five annotators independently tagged metaphor-related words using MIPVU, with adjustments for issues specific to Persian. Their agreement was very high (κ = 0.952). An initial count shows that about 13.1% of lexical units are metaphor-related. Academic texts are the most metaphor-dense and fiction the least.

The corpus supports descriptive and cross-linguistic metaphor research on Persian. It also provides data for training and evaluating machine learning models and LLMs on automatic metaphor identification, a task where current language models still often fail.

## Key points
- **Size and registers:** PerMet 1.0 contains 120,343 tokens / 99,079 lexical units, drawn from five text types: news, fiction, academic prose, spoken language and social media posts.
- **Data collection:**
  - The academic part draws on the Ferdowsi Annotated Academic Language Corpus and on scraped Persian journal articles in four fields: engineering, medical sciences, natural sciences and humanities.
  - The fiction part includes 32 random samples from four Persian novels.
- **Tools:** BeautifulSoup for scraping, Google Vertex AI for OCR, and the Avanegar speech-to-text tool for transcription.
- **Annotation:** five independent annotators applied a Persian-adapted MIPVU, reaching inter-annotator agreement of κ = 0.952.
- **Metaphor rates:** 13.1% of lexical units are metaphor-related. By register, the share ranks academic > news > social media > spoken > fiction.

*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/)

Topics: [Treebanks](https://md.research.elamur.ai/free/topics/treebanks/)

## Cite

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

```bibtex
@inproceedings{miri2026introducing,
  title = {{Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian}},
  author = {Miri, Mohammad Saeid},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
  year = {2026},
  doi = {10.63317/26xmdq7f998f},
  url = {https://doi.org/10.63317/26xmdq7f998f}
}
```

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