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Portho: A Corpus-Based Resource of Orthographic Neighbors in European Portuguese

Paper · 2026 · Eugénio Ribeiro, David Antunes, Nuno Mamede et al.

Summary

European Portuguese has no flexible, easily accessible source of orthographic neighbor (ON) information. PORLEX offers only a narrow set of features, and P-PAL is currently offline and was not built for programmatic use. The authors build PORTHO from lexical frequencies in the Linguateca AC/DC corpora. They cleaned over a million word forms with the STRING NLP Chain, dropping misspellings, punctuation, numerals, acronyms, proper and compound nouns, and single characters, and kept only forms occurring at least 100 times. With NLTK they computed pairwise Levenshtein and Damerau-Levenshtein distances. From these they derived three progressively looser neighbor sets, along with neighborhood counts, frequency-based statistics and graded orthographic distance (OD) measures.

The resource was tested as a source of document-level features for text complexity classification on the iRead4Skills corpus. ON information alone stays below 50% accuracy. Even so, combining all PORTHO features gives the best and most stable results among the ON-based configurations, outperforms PORLEX, and comes within about five points of the full iRead4Skills feature set. PORTHO is publicly released for psycholinguistics, readability modeling and Portuguese NLP.

Key points

  • PORTHO covers 43,429 European Portuguese surface forms. They were selected from more than one million AC/DC corpus forms using STRING-based filtering and a minimum frequency of 100.
  • It has three neighbor definitions: Coltheart (same length, LD of 1), Levenshtein (LD of 1) and Damerau-Levenshtein (adds transpositions). It also includes graded OD features (OLD and ODLD).
  • On iRead4Skills complexity classification (averaged over 20 runs), the full ON+OD feature set reached 49.97% validation accuracy and 43.08% test accuracy. PORLEX features reached 43.12% and 40.06%; the full iRead4Skills feature set reached 54.53% and 49.53%.
  • OD features alone generalized to the test set better than ON features. Combining the two raised validation scores but showed signs of overfitting.
  • Planned extensions are adding OUP and spread metrics, building a lemma-based ON resource, and building a phonological neighbor resource.

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, topics and concepts

📚 Shelves 2The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 works

Cite

Cite as Eugénio Ribeiro, David Antunes, Nuno Mamede and Jorge Baptista. 2026. Portho: A Corpus-Based Resource of Orthographic Neighbors in European Portuguese. Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 1.

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

@inproceedings{ribeiro2026portho,
  title = {{Portho: A Corpus-Based Resource of Orthographic Neighbors in European Portuguese}},
  author = {Eugénio Ribeiro, David Antunes, Nuno Mamede and Jorge Baptista},
  booktitle = {Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 1},
  year = {2026},
  url = {https://aclanthology.org/2026.propor-1.40/}
}

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