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# Domain-Dependent Detection of Light Verb Constructions

**Authors:** István Nagy T., Gábor Berend, György Móra, Veronika Vincze · **Year:** 2011 · **Venue:** Proceedings of the Student Research Workshop associated with RANLP 2011 **Link:** [aclanthology.org/R11-2001](https://aclanthology.org/R11-2001/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**2** citations](https://openalex.org/works?filter=cites:W2250899493) openalex · 2026-10-18[Proceedings of the Second Student Research Workshop associated with RANLP 2011](https://aclanthology.org/volumes/R11-2/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/R11-2001/)
- [PDF](https://aclanthology.org/R11-2001.pdf)
- [OpenAlex](https://openalex.org/W2250899493)

**Authors (4)**

1. [István T. Nagy](https://openalex.org/A5076158859) [ORCID](https://orcid.org/0000-0001-8159-5998) · h 8 · 279 citations · 64 works
2. [Gábor Berend](https://openalex.org/A5020987552) [ORCID](https://orcid.org/0000-0002-3845-4978) · h 12 · 562 citations · 110 works
3. [György Móra](https://openalex.org/A5049533279) h 8 · 1010 citations · 17 works
4. [Veronika Vincze](https://openalex.org/A5089012873) [ORCID](https://orcid.org/0000-0002-9844-2194) · h 26 · 3142 citations · 217 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

The paper detects light verb constructions (LVCs), such as "take a decision", and checks whether methods built for one domain carry over to another. The source domain is a Wikipedia set with 368 LVC occurrences; the target is a parallel corpus with everyday topics (magazines and novels), where the authors drop "have" and "go" from the light-verb list and add "pay" and "catch". Rule-based features are the most frequent verb, a noun suffix, and whether the noun is deverbal. A machine-learning approach is tried too. On the source domain the best single feature is most-frequent-verb at 41.94% F, but on the target it falls to 24.67%. Adapting the rules adds 1.5 F points on average, and 6.17 for the most-frequent-verb feature. Syntactic information adds 2.58 and 2.45 points on the two domains.

## Ideas

- I1. A light-verb rule in `en/src/expert.rs`: a light verb from a short list as the head of a verb-object pair with a deverbal noun, using the intersection the paper finds most precise. Measure: F on EWT test light-verb cases, against a POS-pattern baseline, two identical runs.
- I2. Domain transfer probe: train the Mova rule on one EWT genre and test on another; the paper's drop from 41.94 to 24.67 is the size of effect to look for. Measure: the drop per genre. GUM-based sets are NC, so they are test only.
- I3. Keep the light-verb list in `data/lemmas.tsv` as a versioned file, and check its change with a two-run comparison, as the paper's list change shows how much the list matters.

## For Mova

The chapter is [19. The lexicon: vocabulary, multiword expressions and register](https://md.mova.elamur.ai/free/en/docs/languages/en/19-lexicon-mwe-register/), with [37. Register and variation](https://md.mova.elamur.ai/free/en/docs/languages/en/37-register-and-variation/) for the domain effect. The code is `en/src/expert.rs` (the rule) and `en/src/ctx.rs` (genre as context). The paper's corpora are not Mova data; the Wikipedia set is CC-licensed but NC-type here, so use it for tests only.

## Cite

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

```
@inproceedings{nagy2011domain,
  title = {{Domain-Dependent Detection of Light Verb Constructions}},
  author = {Nagy, István T. and Berend, Gábor and Móra, György and Vincze, Veronika},
  booktitle = {Proceedings of the Second Student Research Workshop associated with RANLP 2011},
  year = {2011},
  url = {https://aclanthology.org/R11-2001/}
}
```

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## References

20 references, 3 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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