Lemmatisation, etymology and information overload on English and Swedish editions of Wiktionary

What it is about

The paper compares how the English and Swedish Wiktionary editions lay out an entry, and how each decides what counts as one headword (lemmatisation). English Wiktionary (en.wikt) follows the etymological approach: homographs of different origin get separate etymology sections above the definitions, so one word can be split into several headings. Swedish Wiktionary (sv.wikt) follows the formal-grammatical approach: one entry per form and part of speech, with etymology nested under each definition. The argument is that both layouts cause information overload, of different kinds: en.wikt fragments definitions across etymology sections, while sv.wikt crowds non-semantic material into each definition. The counts given are descriptive: en.wikt has about 2.6 million entries and 6,000 active editors; sv.wikt has 356,000 entries and 170 active editors. The paper runs no user study.

Ideas

I1. en/src/dict.rs and world/src/dictionary.rs: when a headword has senses of different origin (the paper's "bore" as drill and as tedious), keep one entry per origin with an enum ID, and one entry per part of speech otherwise. Measure the number of split entries and the school answer accuracy before and after.
I2. Put non-semantic material (etymology, derived forms) behind a separate field in the pupil dictionary, so that the sense lines carry only meaning and examples. Measure the SLM student's multiple-choice accuracy with and without the extra fields; a drop would show that the fields are needed for the lesson.
I3. Define a deterministic overload count: for each sense, the number of non-semantic tokens shown with it. Report the mean per entry on the school dictionary and track it across builds.

For Mova

The code is en/src/dict.rs (the lemma and sense table) and world/src/dictionary.rs (the school dictionary). The English chapter for this is 19. The lexicon: vocabulary, multiword expressions and register. The paper's examples are for layout and lemmatisation, not for English grammar; its main use for Mova is the design question of how to split homographs, and the overload count is a measure that Mova can run without any licensed data.

Cite

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

@inproceedings{verdizade2021lemmatisation,
  title = {{Lemmatisation, etymology and information overload on English and Swedish editions of Wiktionary}},
  author = {Verdizade, Allahverdi},
  booktitle = {eLex 2021, pp. 463–478},
  year = {2021},
  url = {https://elex.link/elex2021/proceedings-download/}
}

References

14 references, 0 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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Wolfer, S. & Müller-Spitzer, C. (2016). How many people constitute a crowd and what do they do? Quantitative analyses of revisions in the English and German Wiktionary editions. Lexikos, 26, pp. 347–371. This work is licensed under the Creative Commons Attribution ShareAlike 4.0 International License. http://creativecommons.org/licenses/by-sa/4.0/ ↗

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