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PARSEME 2.0 Multilingual Corpus of Multiword Expressions

Summary

Multiword expressions (MWEs), such as idioms, compounds and fixed function-word sequences, are hard for NLP because their meaning cannot be predicted from their parts. Language models tend to memorize them rather than generalize. Cross-lingual research has also been held back by a lack of comparable annotated data. This paper presents PARSEME 2.0, a manually annotated multilingual corpus. The four earlier releases covered only verbal MWEs; this edition covers every syntactic class: verbal, nominal, adjectival, adverbial and functional. Annotators follow shared guidelines structured as decision diagrams built from linguistic tests, which mostly check lexical and morphosyntactic rigidity. Identical test answers therefore lead to identical labels. The typology has 18 categories, and the texts have UD-compatible morphosyntactic annotation. The resource spans 17 languages and almost 5 million tokens and is released under open licenses. Baseline experiments with a prompt-based identification system show that general-purpose LLMs lack the knowledge to solve MWE identification. This makes the corpus a key benchmark and training resource, including for Ukrainian, which is newly added.

Key points

  • Corpus size: about 5M tokens, more than 250,000 sentences and over 140,000 MWE annotations, organized into 18 MWE categories.
  • Languages: 17 in total. Ten are carried over from earlier editions (fr, el, he, fa, pl, pt, ro, sl, sv, sr). Seven are new: Dutch, Egyptian, Georgian, Ancient Greek, Japanese, Latvian and Ukrainian (uk). Marathi is still in the release pipeline.
  • Previous editions 1.0–1.3 were limited to verbal MWEs and covered up to 26 languages. The 2.0 guidelines extend the verbal branch from 1.3 and draw heavily on the French Sequoia flowchart guidelines.
  • Team for 2.0: 21 Language Leaders, 48 annotators (native speakers except for the ancient languages and French) and 5 core experts. More than 240 people have contributed across all editions, supported by the COST actions IC1207 and CA21167 (UniDive).
  • The corpus is openly licensed and available at hdl.handle.net/11372/LRT-6123. In baseline tests, a prompt-based identification system built on generic LLMs performed inadequately.

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

Cited by

2 papers of our library cite it (of the 140673 whose bibliographies we read); 1 of them have a page here, 1 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/2iy5qf38yhay

@inproceedings{savary2026parseme,
  title = {{PARSEME 2.0 Multilingual Corpus of Multiword Expressions}},
  author = {Savary, Agata and Scholivet, Manon and Ramisch, Carlos and Nakamura, Takuya and Bilinski, Eric and Stymne, Sara and Giouli, Voula and Markantonatou, Stella and Pais, Vasile and Mitrofan, Maria and Estève, Louis and Guillaume, Bruno and Mititelu, Verginica Barbu and Čibej, Jaka and Hernández, Roberto Díaz and Fendel, Victoria and Gantar, Polona and Kanishcheva, Olha and Krstev, Cvetana and Liebeskind, Chaya and Lobzhanidze, Irina and Marković, Aleksandra M. and Nešpore-Bērzkalne, Gunta and Pagano, Adriana S. and Shamsfard, Mehrnoush and Stankovic, Ranka and Tajalli, Vahide and Tiberius, Carole and Padhye, Aakanksha},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
  year = {2026},
  doi = {10.63317/2iy5qf38yhay},
  url = {https://doi.org/10.63317/2iy5qf38yhay}
}

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