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Semantic primes in historical languages. The identification of the Old English exponent for DO

Paper · 2020 · Raquel Mateo Mendaza

Summary

This article asks which Old English verb best expresses DO, one of the semantic primes of the Natural Semantic Metalanguage (NSM). Old English has no living speakers, so a translation cannot be checked with native intuition. The author instead relies on indirect, corpus-based evidence. Candidates meaning "to do" were gathered from the HTOED: (ge)dōn, (ge)þēon, (ge)drēogan and (ge)macian. Each was then tested on four kinds of criteria: textual frequency, morphology, semantics and syntactic complementation, the last read against NSM valency options. The data came from the Nerthus lexical database, the Dictionary of Old English and the Dictionary of Old English Corpus.

(ge)dōn outperforms the other verbs on every criterion and is chosen as the exponent. (ge)macian is its closest rival, but its meaning is narrower and centres on the product and process of making. Dialectal and historical evidence supports the choice. The study completes the author's series on the action/event primes, after TOUCH, HAPPEN and MOVE. It also proposes a refined, reusable procedure for finding primes in historical languages.

Key points

  • The NSM inventory now has 65 primes in 17 categories, and prime exponents have been studied in more than 70 living languages.
  • The canonical frame for DO has an obligatory agent, an action complement and an associated time adjunct, and it can also take a manner variant. Its optional valency slots are patient, instrument and comitative.
  • The four candidates were (ge)dōn, (ge)þēon, (ge)drēogan and (ge)macian, and (ge)dōn scored best on all four criteria.
  • Following Kuhn (1980), (ge)dōn appears in all OE dialects. (ge)macian is limited to West Saxon and is not attested before the Alfredian period.
  • Two methodological lessons come from the author's earlier papers:
    • The frequency criterion is distorted by polysemy and homonymy, while the semantic and syntactic tests give steadier results.
    • In this study, one candidate chosen on etymological and grammatical grounds served as the benchmark for comparing the others.

Interesting ideas

  • I1. Judge a candidate word by several independent tests (frequency, morphology, meaning, argument structure) rather than by counts alone, because each test fails in different ways.
  • I2. Raw frequency is unreliable when a word is polysemous or has homonyms, so syntactic and semantic evidence should outweigh it.
  • I3. Define a core predicate by a minimal frame plus a list of optional valency slots, each named by a semantic role. This gives a compact, language-neutral description of what a verb can combine with.
  • I4. Separate a general "perform an action" verb from a narrower "produce a result" verb (do vs. make) by checking whether the meaning focuses on the outcome or on the act itself.
  • I5. When candidates are many, pick one strong benchmark on prior grounds and compare every other candidate against it on each criterion. This narrows the analysis and makes each decision explicit.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (world): When mapping English verbs onto ontology concepts or VerbNet classes, combine frequency, sense and frame evidence, and record which test decided the mapping so it stays explainable.
  • I2 (learn): In silver-data agreement, treat high-frequency but ambiguous lemmas as low-confidence unless frame or argument evidence agrees with the frequency signal.
  • I3 (frames): Encode basic action predicates like DO and HAPPEN as minimal frames with optional patient, instrument and comitative slots, so the frame filler knows which roles are required and which are optional.
  • I4 (world): Model "do" events as generic actions and "make" events as creating a new entity, so the world of the text adds a new object only for make-type verbs.
  • I5 (learn): In evaluation, compare a new parser or rule set against one fixed reference witness criterion by criterion, instead of ranking all variants at once.

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

 Institutions

🎓Universidad de La RiojaLogroño · Spain24 works · 125 citations

 Fields, topics and concepts

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPsychology · 1,552 worksExperimental and Cognitive Psychology · 870 works

🧭 Topics 2Research subjects and languages the work is about.English · 2,263 worksHistorical linguistics & language change · 249 works

Cite

Cite as Raquel Mateo Mendaza. 2020. Semantic primes in historical languages. The identification of the Old English exponent for DO. Journal of English Studies 18.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18172/jes.4467

@article{mendaza2020semantic,
  title = {{Semantic primes in historical languages. The identification of the Old English exponent for DO}},
  author = {Raquel Mateo Mendaza},
  journal = {Journal of English Studies 18},
  year = {2020},
  doi = {10.18172/jes.4467},
  url = {https://doi.org/10.18172/jes.4467}
}

References

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