---
title: "UniMorph 2.0: Universal Morphology — paper by Kirov et al. (2018)"
description: "Most of the world's languages have rich inflection, yet NLP systems often handle it poorly. 18 references, cited by 114 papers here."
authors: ["Christo Kirov", "Ryan Cotterell", "John Sylak-Glassman", "Géraldine Walther", "Ekaterina Vylomova", "Patrick Xia", "Manaal Faruqui", "Sabrina J. Mielke", "Arya McCarthy", "Sandra Kübler", "David Yarowsky", "Jason Eisner", "Mans Hulden"]
year: 2018
venue: "Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)"
source: "https://aclanthology.org/L18-1293/"
arxiv: "1810.11101"
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/en/papers/kirov-2018-unimorph-2-0-universal-morphology/"
---
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# UniMorph 2.0: Universal Morphology

**Authors:** [Christo Kirov](https://md.research.elamur.ai/free/en/authors/christo-kirov/), [Ryan Cotterell](https://md.research.elamur.ai/free/en/authors/ryan-cotterell/), [John Sylak-Glassman](https://md.research.elamur.ai/free/en/authors/john-sylak-glassman/), [Géraldine Walther](https://md.research.elamur.ai/free/en/authors/geraldine-walther/), [Ekaterina Vylomova](https://md.research.elamur.ai/free/en/authors/ekaterina-vylomova/), [Patrick Xia](https://md.research.elamur.ai/free/en/authors/patrick-xia/), [Manaal Faruqui](https://md.research.elamur.ai/free/en/authors/manaal-faruqui/), [Sabrina J. Mielke](https://md.research.elamur.ai/free/en/authors/sabrina-j-mielke/), [Arya McCarthy](https://md.research.elamur.ai/free/en/authors/arya-d-mccarthy/), [Sandra Kübler](https://md.research.elamur.ai/free/en/authors/sandra-kubler/), [David Yarowsky](https://md.research.elamur.ai/free/en/authors/david-yarowsky/), [Jason Eisner](https://md.research.elamur.ai/free/en/authors/jason-eisner/) and [Mans Hulden](https://md.research.elamur.ai/free/en/authors/mans-hulden/) · **Year:** 2018 · **Venue:** [Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)](https://md.research.elamur.ai/free/en/venues/lrec/) ([LREC 2018](https://md.research.elamur.ai/free/en/venues/lrec/2018/)) · **Publisher:** [European Language Resources Association (ELRA)](https://md.research.elamur.ai/free/en/publishers/european-language-resources-association-elra/) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/L18-1293/) · [PDF](https://aclanthology.org/L18-1293.pdf) · [arXiv 1810.11101](https://arxiv.org/abs/1810.11101) · [OpenAlex](https://openalex.org/W2964065120)

**Citations:** 109 citations (OpenAlex, 2026-10-14) · [114](https://md.research.elamur.ai/free/en/papers/kirov-2018-unimorph-2-0-universal-morphology/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## Summary
Most of the world's languages have rich inflection, yet NLP systems often handle it poorly. The UniMorph project collects morphological data with uniform annotation: each word form is linked to a lemma and a set of features from the universal UniMorph schema. Version 1.0 automatically extracted paradigms from Wiktionary tables using heuristics and therefore contained many systematic errors. In version 2.0, the authors stopped correcting the automatic parse and changed their approach. The HTML tables for each language are grouped by structure using pandas. A human annotates only one sample from each group, and the annotation is automatically propagated to all tables with the same layout. In this way, three annotators prepared data for 47 languages within a few days, and native speakers or experts then verified the result. Together with sources outside Wiktionary, the resource covers 52 languages, including low-resource ones such as Quechua, Navajo and Haida. Lists of lemmas without tables and generated English glosses for word forms have also been added. The data are open and served as the basis for the CoNLL–SIGMORPHON 2017 Shared Task, which makes the resource important for multilingual morphology.

## Key points
- **The UniMorph schema:** more than 200 basic features across 23 dimensions, including rare categories such as evidentiality and switch-reference. Distinctions not covered by the schema, as well as free variants of forms, are marked with language-specific LGSPEC labels.
- **Comparison with 1.0:** version 1.0 contained 952,530 lemmas from 350 languages, but with a large number of errors. Previously, only 8 languages had been corrected manually for SIGMORPHON 2016. In 2.0, the Wiktionary data for 47 languages replaced the corresponding data from 1.0.
- **Sources outside Wiktionary:** Khaling, Kurmanji and Sorani were taken from the Alexina project. The Haida data were prepared by Jordan Lachler. Basque was extracted from a finite-state analyzer. All these data were converted to the UniMorph schema.
- **English glosses:** they are generated from templates with Penn Treebank tags and from bilingual dictionaries, e.g. «comprábamos» → «(we) were buying». Glosses are available for 10 languages, including Ukrainian: 20,288 word forms and 41,590 glosses. Hungarian has the largest volume: 2,814,006 word forms.
- **Community:** the data are released incrementally under an open license via unimorph.github.io. Each language has a public issue tracker. The project is organized on the model of UD.

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

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## Cite

Cite as: Christo Kirov, Ryan Cotterell, John Sylak-Glassman, Géraldine Walther, Ekaterina Vylomova, Patrick Xia, Manaal Faruqui, Sabrina J. Mielke, Arya McCarthy, Sandra Kübler, David Yarowsky, Jason Eisner and Mans Hulden. 2018. UniMorph 2.0: Universal Morphology. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).

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

```bibtex
@inproceedings{kirov2018unimorph,
  title = {{UniMorph 2.0: Universal Morphology}},
  author = {Christo Kirov, Ryan Cotterell, John Sylak-Glassman, Géraldine Walther, Ekaterina Vylomova, Patrick Xia, Manaal Faruqui, Sabrina J. Mielke, Arya McCarthy, Sandra Kübler, David Yarowsky, Jason Eisner and Mans Hulden},
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  doi = {10.63317/3rq3n9kr4gk8},
  eprint = {1810.11101},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.63317/3rq3n9kr4gk8}
}
```

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## References

18 references, 6 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 29 October 2026*