---
title: "Intervention effects in NPI licensing — paper by Denić et al. (2018)"
description: "Chierchia proposed that these interveners disrupt licensing because their implicatures make the environment no longer… 36 references."
authors: ["Milica Denić", "Emmanuel Chemla", "Lyn Tieu"]
year: 2018
venue: "Glossa: a journal of general linguistics"
source: "https://www.glossa-journal.org/article/id/5017/"
doi: "10.5334/gjgl.388"
licence: "CC BY 4.0"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/denic-2018-intervention-effects-npi-licensing-quantitative/"
---
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# Intervention effects in NPI licensing: A quantitative assessment of the scalar implicature explanation

**Authors:** Milica Denić, [Emmanuel Chemla](https://md.research.elamur.ai/free/en/authors/emmanuel-chemla/) and [Lyn Tieu](https://md.research.elamur.ai/free/en/authors/lyn-tieu/) · **Year:** 2018 · **Venue:** [Glossa: a journal of general linguistics](https://md.research.elamur.ai/free/en/venues/glossa-a-journal-of-general-linguistics/) ([Glossa a journal of general linguistics 2018](https://md.research.elamur.ai/free/en/venues/glossa-a-journal-of-general-linguistics/2018/)) · **Publisher:** [Ubiquity Press](https://md.research.elamur.ai/free/en/publishers/ubiquity-press/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://doi.org/10.5334/gjgl.388) · [PDF](https://www.glossa-journal.org/article/5017/galley/12119/download) · [DOI 10.5334/gjgl.388](https://doi.org/10.5334/gjgl.388) · [OpenAlex](https://openalex.org/W2802043295)

**Citations:** 4 citations (OpenAlex, 2026-10-14)

## Summary
The paper asks whether scalar implicatures can account for the way certain elements block the licensing of negative polarity items (NPIs), a phenomenon known as intervention. Intervention effects are cases where an element such as *every* or *and*, placed between a licensor like negation and an NPI like *any*, makes the sentence degraded. Chierchia proposed that these interveners disrupt licensing because their implicatures make the environment no longer downward-entailing.

The authors ran five online experiments. Experiment 1 used graded acceptability ratings and found that intervention sentences are not categorically bad. They are rated better than sentences with unlicensed NPIs, and judgments vary. This weakens the classic objection that implicatures are optional while intervention seems absolute.

Experiments 2–5 then tested whether people who compute implicatures more often also show stronger intervention effects. They used picture selection, a covered picture task, implicature training, and repair of intervention sentences. Only the repair task, which measured both phenomena at once, supported the link.

The result is a mixed picture. It is relevant to any theory, grammatical or processing-based, that must explain graded judgments of intervention.

## Key points
- Five experiments in total; data and R analysis scripts are publicly released on semanticsarchive.net.
- Experiment 1 recruited 54 Amazon Mechanical Turk participants, with one excluded as a non-native speaker. They rated sentences from 1 to 5 on the Ibex platform, framed as sentences produced by Zap, an alien learning English.
- Universal NPs (*every rabbit*) and conjunction (*both… and*) act as interveners, while definite NPs (*the rabbits*) do not. In all these cases the environment remains logically downward-entailing.
- Experiments 2 and 3 (picture selection and covered picture task) and Experiment 4 (training participants to derive or avoid implicatures) found no correlation between implicature rates and sensitivity to intervention.
- Experiment 5 measured implicatures and intervention together through repair strategies. Participants seemed to rescue intervention sentences by switching off the implicature, which is the only positive evidence for the SI theory.

## Interesting ideas
- Instead of assuming a construction is simply ungrammatical, measure graded acceptability and compare it with a truly ill-formed baseline; "bad" may turn out to be "worse but rescuable."
- Two optional phenomena can be linked by asking whether their variability co-occurs, not only whether both exist. Correlating them across separate tasks can miss the link, while measuring them on the same item can reveal it.
- How speakers repair a defective sentence shows which reading they had to give up to make it interpretable.
- Minimal pairs that differ only in one element (*every* vs *the*) separate the true cause from general sentence complexity.
- Licensing is defined semantically, through whether set-to-subset inferences hold, and implicatures can silently change that monotonicity.

## For Mova

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

- **I1** (frames): the NPI/intervention checker in prag could return a graded penalty instead of rejecting the parse, so a sentence like *didn't give every rabbit any juice* still gets frames with a lowered confidence.
- **I2** (learn): when testing whether one module's choice drives another's, evaluate both decisions on the same sentence rather than correlating separate benchmark scores.
- **I3** (learn): self-induced repair rules could log which interpretive option, such as a strengthened implicature reading, was dropped to rescue a sentence, giving an explainable trace of the repair.
- **I4** (learn): build negative-control sets of such pairs so that improvements on intervention-like structures can be attributed to the targeted rule and not to length or depth.
- **I5** (world): keep the literal and the implicature-enriched meaning as two separate states in the text world, and check inferences like downward entailment against each one, so answers can explain which reading they relied on.

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

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## Cite

Cite as: Milica Denić, Emmanuel Chemla and Lyn Tieu. 2018. Intervention effects in NPI licensing: A quantitative assessment of the scalar implicature explanation. Glossa: a journal of general linguistics.

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

```bibtex
@article{denic2018intervention,
  title = {{Intervention effects in NPI licensing: A quantitative assessment of the scalar implicature explanation}},
  author = {Milica Denić, Emmanuel Chemla and Lyn Tieu},
  journal = {Glossa: a journal of general linguistics},
  year = {2018},
  doi = {10.5334/gjgl.388},
  url = {https://doi.org/10.5334/gjgl.388}
}
```

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## References

36 references, 2 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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34. How to cite this article: Denić, Milica, Emmanuel Chemla and Lyn Tieu. 2018. [Intervention effects in NPI licensing: A quantitative assessment of the scalar implicature explanation](https://md.research.elamur.ai/free/en/papers/denic-2018-intervention-effects-npi-licensing-quantitative/). Glossa: a journal of general linguistics 3(1): 49. 1–27, DOI: https://doi.org/10.5334/gjgl.388 [↗](https://doi.org/10.5334/gjgl.388)
35. Accepted: 14 January 2018 [find](https://scholar.google.com/scholar?q=Accepted%3A+14+January+2018)
36. Copyright: © 2018 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/). Glossa: a journal of general linguistics is a peer-reviewed open access journal published by Ubiquity Press. OPEN ACCESS [↗](http://creativecommons.org/licenses/by/4.0/)

*Updated 1 November 2026*