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Edition 1.1 of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions

Summary

Verbal multiword expressions (VMWEs) are idiomatic combinations headed by a verb, such as light verb constructions or verb-particle constructions. They are hard for NLP systems because their lexicalized parts can be split apart, inflected, or seldom seen in training data. This paper describes the 2018 round (edition 1.1) of the PARSEME shared task, where systems must locate VMWEs in running text.

After the 2017 campaign, contributors raised about 80 guideline issues, and the organizers used them to revise the multilingual annotation methodology. The category inventory was redesigned, and annotators now apply one unified decision tree instead of a two-stage identify-then-classify procedure. Annotated corpora were extended or newly built for 20 languages, and the evaluation gained phenomenon-specific measures.

Seventeen systems from 12 teams in 9 countries participated, well above the previous edition. Systems struggled most with VMWEs never observed in training. The authors argue that solving this will likely require large lexicons or semi/unsupervised methods. The resulting corpora give a consistent cross-lingual benchmark for VMWE research.

Key points

  • The revised typology has two universal categories: LVC (split into LVC.full and LVC.cause) and VID. It also has quasi-universal categories (IRV; VPC.full and VPC.semi; MVC), the Italian-specific LS.ICV, and an optional experimental IAV category.
  • Participation grew from 7 systems in 2017 to 17 in 2018, and 11 submissions covered 19 languages. The 1.0 edition had covered 18 languages.
  • Average F1-MWE gaps across systems:
    • about 50 points (45–56) for seen vs. unseen-in-train VMWEs
    • 27 points for multi-token vs. single-token VMWEs
    • 20 points for identical vs. variant-of-train VMWEs
    • 17 points for continuous vs. discontinuous VMWEs
  • Guideline issues, data and system outputs are public on GitLab (parseme/sharedtask-guidelines, parseme/sharedtask-data). The authors plan further work on the MVC guidelines and the IAV category, and want future editions to cover non-verbal MWEs.

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

75 papers of our library cite it (of the 140673 whose bibliographies we read); 8 of them have a page here, 67 not yet.

Cite

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

@inproceedings{ramisch2018edition,
  title = {{Edition 1.1 of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions}},
  author = {Ramisch, Carlos and Cordeiro, Silvio Ricardo and Savary, Agata and Vincze, Veronika and Mititelu, Verginica Barbu and Bhatia, Archna and Buljan, Maja and Candito, Marie and Gantar, Polona and Giouli, Voula and Güngör, Tunga and Hawwari, Abdelati and Iñurrieta, Uxoa and Kovalevskaitė, Jolanta and Krek, Simon and Lichte, Timm and Liebeskind, Chaya and Monti, Johanna and Escartín, Carla Parra and QasemiZadeh, Behrang and Ramisch, Renata and Schneider, Nathan and Stoyanova, Ivelina and Vaidya, Ashwini and Walsh, Abigail},
  booktitle = {Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018)},
  year = {2018},
  url = {https://aclanthology.org/W18-4925/}
}

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