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# MorphoLex: A derivational morphological database for 70,000 English words

**Authors:** Claudia H. Sánchez-Gutiérrez, Hugo Mailhot, S. Hélène Deacon, Maximiliano A. Wilson · **Year:** 2018 · **Venue:** Behavior Research Methods **Link:** [doi.org/10.3758/s13428-017-0981-8](https://doi.org/10.3758/s13428-017-0981-8) · **Licence:** Springer open access; the licence is not stated in the PDF — summary only

[**98** citations](https://openalex.org/works?filter=cites:W2767253414) openalex-snapshot · 2026-10-14[**17** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-2018-sanchezgutierrez-morpholex/) of the 140673 papers whose bibliographies we read[Behavior Research Methods 50: 1568–1580 (2018)](https://openalex.org/S137478622)[licence](https://doi.org/10.3758/s13428-017-0981-8)

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**Authors (4)**

1. Claudia H. Sánchez-Gutiérrez
2. [Hugo Mailhot](https://openalex.org/A5069605801) h 3 · 121 citations · 8 works
3. [S. Hélène Deacon](https://openalex.org/A5045812174) [ORCID](https://orcid.org/0000-0002-4792-5137) · h 44 · 7578 citations · 185 works
4. [Maximiliano A. Wilson](https://openalex.org/A5039462396) [ORCID](https://orcid.org/0000-0001-9861-442X) · h 20 · 1358 citations · 123 works

Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart.

## What it is about

The paper presents MorphoLex, a database of derivational morphology for the English Lexicon Project. It segments 68,624 of the 79,672 entries into prefixes, suffixes and bases, and gives six variables for affixes (frequency, family size, percentage of more frequent family words, two productivity values and length) and three for roots. The authors then fit regression models of lexical decision latencies on 4,724 suffixed nouns, each with one root and one suffix. Root frequency and suffix length speed decisions up, while the share of more frequent words in the suffix family slows them down. Root and suffix family size also have facilitatory effects once collinearity is controlled.

## Ideas

- I1. `en/src/morph.rs` and `en/src/lexgen.rs`: add a derivational segmentation table (affix, base, affix family size) next to the lemma and form tables, and check that every suffixed form in `data/forms.tsv` gets a base. Measure the coverage of the 4,724 nouns in the paper's set.
- I2. Productivity as a rule feature: compute the paper's percentage-of-more-frequent-family value for each suffix from the `en` lexicon counts, and test whether it separates the suffix rules that `en morph-eval` gets wrong. Measure lemma accuracy on EWT with and without the feature.
- I3. Test only: use the paper's latency pattern (suffix length, root frequency) as an external check on the morphology module's segmentation choices. The database is not in the build, so only the comparison runs.

## For Mova

The chapter is [17. Derivation II: suffixes](https://md.mova.elamur.ai/free/en/docs/languages/en/17-derivation-suffixes/), with `16-derivation-prefixes.md` for the prefix side. The code is `en/src/morph.rs` and the `en morph-eval` command. The paper's data is a psycholinguistic set, not a treebank; use it for tests and comparisons only, never in what is built. Measure first: lemma accuracy on EWT test for suffixed forms, before and after the segmentation table.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.3758/s13428-017-0981-8](https://doi.org/10.3758/s13428-017-0981-8)

```
@inproceedings{sanchezgutierrez2018morpholex,
  title = {{MorphoLex: A derivational morphological database for 70,000 English words}},
  author = {Sánchez-Gutiérrez, Claudia H. and Mailhot, Hugo and Deacon, S. Hélène and Wilson, Maximiliano A.},
  booktitle = {Behavior Research Methods 50: 1568–1580 (2018)},
  year = {2018},
  doi = {10.3758/s13428-017-0981-8},
  url = {https://doi.org/10.3758/s13428-017-0981-8}
}
```

- [← previous Evaluation of Finite State Morphological Analyzers Based on Paradigm Extraction from Wiktionary](https://md.mova.elamur.ai/free/en/docs/papers/lex-2017-liu-fst-paradigm-extraction-wiktionary/)
- [next → English WordNet 2019 – An Open-Source WordNet for English](https://md.mova.elamur.ai/free/en/docs/papers/lex-2019-mccrae-english-wordnet/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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