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home / papers / 2025 / URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base

URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base

Paper · 2025 · Aditya Khan, Mason Shipton, David Anugraha et al.

Summary

URIEL, queried through the lang2vec tool, is a widely cited source of geographical, phylogenetic and typological language vectors. It has serious gaps. Roughly a third of the languages it can compare have no typological data and silently receive default values. Its distances are pre-computed with poorly documented settings, and some pairs, such as Croatian and Serbian, come out far apart despite being closely related.

The authors build URIEL+ to address these problems. It merges five typological databases after binarizing non-binary features and reconciling overlapping ones, and it adds morphology as a new feature type. Users can choose among three imputation algorithms for missing values. Distances are computed on demand, with configurable aggregation, metric, feature subset and data source, and each distance comes with a confidence score indicating its reliability.

Replicating three downstream systems shows results equal to or better than the original. A case study suggests URIEL+ distances follow an expert typological measure more closely. Overall, the resource makes typological comparison usable for thousands of low-resource languages.

Key points

  • The integrated databases are Grambank, APiCS, eWAVE, SAPhon and BDPROTO. Together they add data for 2898 languages, of which 2858 are low-resource. The knowledge base now covers 8071 languages in total.
  • The number of languages with real data for featural distance rises from 2724 to 4366. In the original URIEL, 1281 of its 4005 distance-ready languages relied entirely on default values.
  • Downstream checks used LangRank (transfer-language selection), LinguAlchemy and ProxyLM (performance prediction). URIEL+ was competitive overall, with clear gains in LangRank's POS and MT subtasks.
  • The case study on Isthmo-Colombian languages compared each resource with the dependency-aware Gower coefficient (G_d) of Hammarström & O'Connor (2013). Kendall correlation improved from −0.05 for URIEL to 0.19 for URIEL+, but the difference was not significant (p = 0.307).
  • Feature coverage remains skewed toward grammar: 474 syntactic and 133 morphological features, versus 30 phonological and 163 inventory features. Script information is still missing. The code is open at github.com/Masonshipton25/URIELPlus.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of TorontoToronto · Canada96 works · 142,007 citations🎓University of MichiganAnn Arbor · United States70 works · 13,693 citations🎓Ontario Tech UniversityOshawa · Canada8 works · 1,554 citations

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPsychology · 1,552 worksExperimental and Cognitive Psychology · 870 works

🧭 Topics 2Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 828 worksKnowledge graphs & ontologies · 192 works

Cite

Cite as Aditya Khan, Mason Shipton, David Anugraha, Kaiyao Duan, Phuong H. Hoang, Eric Khiu, A. Seza Doğruöz and En-Shiun Annie Lee. 2025. URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base. Proceedings of the 31st International Conference on Computational Linguistics.

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

@inproceedings{khan2025uriel,
  title = {{URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base}},
  author = {Aditya Khan, Mason Shipton, David Anugraha, Kaiyao Duan, Phuong H. Hoang, Eric Khiu, A. Seza Doğruöz and En-Shiun Annie Lee},
  booktitle = {Proceedings of the 31st International Conference on Computational Linguistics},
  year = {2025},
  url = {https://aclanthology.org/2025.coling-main.463/}
}

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