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# Unsupervised discovery of morphologically related words based on orthographic and semantic similarity

**Authors:** Marco Baroni, Johannes Matiasek · **Year:** 2002 · **Venue:** Proceedings of the ACL-02 Workshop on Morphological and Phonological Learning **Link:** [aclanthology.org/W02-0606](https://aclanthology.org/W02-0606/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**116** citations](https://openalex.org/works?filter=cites:W1727944201) openalex · 2026-10-19[**28** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2002-baroni-unsupervised-discovery-morphologically-related-words/) of the 140673 papers whose bibliographies we read[Proceedings of the ACL-02 Workshop on Morphological and Phonological Learning](https://aclanthology.org/volumes/W02-06/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/W02-0606/)
- [PDF](https://aclanthology.org/W02-0606.pdf)
- [DOI 10.3115/1118647.1118653](https://doi.org/10.3115/1118647.1118653)
- [OpenAlex](https://openalex.org/W1727944201)

**Authors (3)**

1. [Marco Baroni](https://openalex.org/A5038612405) [ORCID](https://orcid.org/0000-0001-5066-3580) · [Semantic Scholar](https://www.semanticscholar.org/author/145283199) · h 62 · 17016 citations · 218 works
2. [Johannes Matiasek](https://openalex.org/A5050235805) [Semantic Scholar](https://www.semanticscholar.org/author/1916085) · h 10 · 360 citations · 48 works
3. [Harald Trost](https://openalex.org/A5090301030) [Semantic Scholar](https://www.semanticscholar.org/author/1809119) · h 11 · 545 citations · 99 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

The algorithm takes an unannotated corpus and returns a ranked list of probably related word pairs, such as a verb and its past form or a noun and its derived adjective. Two words are paired when they are close both in spelling and in meaning. Spelling is measured by minimum edit distance, and meaning by mutual information between the words in the corpus. The method does not model morphemes as concatenation, and it does not use affix frequencies. The authors test German and English. Precision, the share of correct pairs above a cut-off on the ranked list, is high at the top of the list: about 97% for the first 500 German pairs, out of 5,279 in total. The paper also discusses the types of morphological patterns that appear in the output.

## Ideas

- I1. `en/src/lexgen.rs`: rank candidate pairs of English words in `data/forms.tsv` that are not yet linked, by edit distance and by a co-occurrence score from a raw corpus. Measure precision at 500 and 1,000 pairs against the existing links in the dictionary.
- I2. Add the paper's transitivity idea: if a is related to b and b to c, then a and c form a pair. Check on the held-out links of `data/lemmas.tsv` whether the transitive pairs are right more often than the ranking score alone.
- I3. Report precision at fixed cut-offs in the output of the candidate list, as the paper does, so that the ranking can be compared run to run before any use in the rules of `en/src/morph.rs`.

## For Mova

The code is `en/src/lexgen.rs`, with `en lexicon`. The chapters are [16. Derivation I: prefixes](https://md.mova.elamur.ai/free/en/docs/languages/en/16-derivation-prefixes/) and [17. Derivation II: suffixes](https://md.mova.elamur.ai/free/en/docs/languages/en/17-derivation-suffixes/). The paper's German data is not English, and the English results are only qualitative in the text, so Mova needs its own numbers. Measure first on English held-out links, twice, with the ranking fixed before any change.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.3115/1118647.1118653](https://doi.org/10.3115/1118647.1118653)

```
@inproceedings{baroni2002unsupervised,
  title = {{Unsupervised discovery of morphologically related words based on orthographic and semantic similarity}},
  author = {Baroni, Marco and Matiasek, Johannes and Trost, Harald},
  booktitle = {Proceedings of the ACL-02 Workshop on Morphological and Phonological Learning},
  year = {2002},
  doi = {10.3115/1118647.1118653},
  url = {https://doi.org/10.3115/1118647.1118653}
}
```

- [← previous Knowledge-Free Induction of Inflectional Morphologies](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2001-schone-knowledge-free-induction-inflectional-morphologies/)
- [next → Combining Unsupervised and Supervised Methods for PP Attachment Disambiguation](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2002-volk-combining-unsupervised-supervised-methods-pp/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

16 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. A. Albright and B. Hayes. 1999. An automated learner for phonology and morphology. UCLA manuscript. [find](https://scholar.google.com/scholar?q=A%2E+Albright+and+B%2E+Hayes%2E+1999%2E+An+automated+learner+for+phonology+and+morphology%2E+UCLA+manuscript%2E)
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3. M. Baroni, J. Matiasek and H. Trost. 2002. Wordform-and class-based prediction of the components of German nominal compounds in an AAC system. To appear in Proceedings of COLING 2002. [find](https://scholar.google.com/scholar?q=M%2E+Baroni%2C+J%2E+Matiasek+and+H%2E+Trost%2E+2002%2E+Wordform%2Dand+class%2Dbased+prediction+of+the+components+of+German+nominal+compounds+in+an+AAC+system%2E+To+appear+in+Proceedings+of+COLING+2002%2E)
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11. C. Manning and H. Schütze. 1999. Foundations of statistical natural language processing. MIT Press, Cambridge, MASS. [find](https://scholar.google.com/scholar?q=C%2E+Manning+and+H%2E+Schu%CC%88tze%2E+1999%2E+Foundations+of+statistical+natural+language+processing%2E+MIT+Press%2C+Cambridge%2C+MASS%2E)
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