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        <title>Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian</title>
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    <abstract>Metaphor plays a central role in human language and thought, and corpus-linguistic approaches enable its systematic investigation. Such research requires large, representative collections of metaphor-annotated linguistic data from diverse contexts. Despite the increasing availability of metaphor corpora in various languages, Persian remains underrepresented, with few publicly available resources and no large-scale register-diverse metaphor corpus. This paper introduces PerMet 1.0, a metaphor-annotated corpus for Persian. The corpus consists of approximately 120,000 tokens (about 99,000 lexical units) drawn from five registers: academic, news, fiction, social media, and spoken discourse. Five independent annotators labeled the corpus using Metaphor Identification Procedure Vrije Universiteit (MIPVU), with adaptations for Persian. Inter-annotator agreement showed a high level of consistency (\ensuremathąppa = 0.952), confirming the reliability of the annotation. Preliminary analysis shows that 13.1% of the lexical units are related to metaphor, with the academic register showing the highest proportion, followed by news, social media, spoken, and fiction. PerMet 1.0 offers a foundational resource for research on metaphor in Persian, cross-linguistic comparative studies, and the development and fine-tuning of machine learning or large language models for automatic metaphor identification.</abstract>
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%0 Conference Proceedings
%T Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian
%A Miri, Mohammad Saeid
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F miri-2026-introducing
%X Metaphor plays a central role in human language and thought, and corpus-linguistic approaches enable its systematic investigation. Such research requires large, representative collections of metaphor-annotated linguistic data from diverse contexts. Despite the increasing availability of metaphor corpora in various languages, Persian remains underrepresented, with few publicly available resources and no large-scale register-diverse metaphor corpus. This paper introduces PerMet 1.0, a metaphor-annotated corpus for Persian. The corpus consists of approximately 120,000 tokens (about 99,000 lexical units) drawn from five registers: academic, news, fiction, social media, and spoken discourse. Five independent annotators labeled the corpus using Metaphor Identification Procedure Vrije Universiteit (MIPVU), with adaptations for Persian. Inter-annotator agreement showed a high level of consistency (\ensuremathąppa = 0.952), confirming the reliability of the annotation. Preliminary analysis shows that 13.1% of the lexical units are related to metaphor, with the academic register showing the highest proportion, followed by news, social media, spoken, and fiction. PerMet 1.0 offers a foundational resource for research on metaphor in Persian, cross-linguistic comparative studies, and the development and fine-tuning of machine learning or large language models for automatic metaphor identification.
%R 10.63317/26xmdq7f998f
%U https://aclanthology.org/2026.lrec-1.379/
%U https://doi.org/10.63317/26xmdq7f998f
%P 4835-4845

Markdown (Informal)

[Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian](https://aclanthology.org/2026.lrec-1.379/) (Miri, LREC 2026)

• Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian (Miri, LREC 2026)

ACL

• Mohammad Saeid Miri. 2026. Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 4835–4845, Palma de Mallorca, Spain. ELRA Language Resource Association.