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# VerbNet Representations: Subevent Semantics for Transfer Verbs

**Authors:** [Susan Windisch Brown](https://md.mova.elamur.ai/free/en/docs/papers/authors/susan-windisch-brown/), [Julia Bonn](https://md.mova.elamur.ai/free/en/docs/papers/authors/julia-bonn/), [James Gung](https://md.mova.elamur.ai/free/en/docs/papers/authors/james-gung/), [Annie Zaenen](https://md.mova.elamur.ai/free/en/docs/papers/authors/annie-zaenen/), [James Pustejovsky](https://md.mova.elamur.ai/free/en/docs/papers/authors/james-pustejovsky/), [Martha Palmer](https://md.mova.elamur.ai/free/en/docs/papers/authors/martha-palmer/) · **Year:** 2019 · **Venue:** DMR 2019 (First International Workshop on Designing Meaning Representations) **Link:** [aclanthology.org/W19-3318](https://aclanthology.org/W19-3318/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**16** citations](https://openalex.org/works?filter=cites:W2972809615) openalex · 2026-10-19[**11** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/brown-2019-verbnet-representations-subevent-semantics-transfer/) of the 140673 papers whose bibliographies we read[Proceedings of the First International Workshop on Designing Meaning Representations](https://aclanthology.org/volumes/W19-33/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/W19-3318/)
- [PDF](https://aclanthology.org/W19-3318.pdf)
- [DOI 10.18653/v1/w19-3318](https://doi.org/10.18653/v1/w19-3318)
- [OpenAlex](https://openalex.org/W2972809615)

**Authors (6)**

1. [Susan Windisch Brown](https://openalex.org/A5015929703) [Semantic Scholar](https://www.semanticscholar.org/author/1783500) · h 12 · 353 citations · 48 works
2. [Julia Bonn](https://openalex.org/A5088874459) [Semantic Scholar](https://www.semanticscholar.org/author/19331592) · h 8 · 169 citations · 24 works
3. [James Gung](https://openalex.org/A5057625092) [Semantic Scholar](https://www.semanticscholar.org/author/2411024472) · h 7 · 144 citations · 31 works
4. [Annie Zaenen](https://openalex.org/A5026833137) [Semantic Scholar](https://www.semanticscholar.org/author/1809816) · h 25 · 3821 citations · 122 works
5. [James Pustejovsky](https://openalex.org/A5012141433) [ORCID](https://orcid.org/0000-0003-2233-9761) · [Semantic Scholar](https://www.semanticscholar.org/author/1707726) · h 55 · 16153 citations · 425 works
6. [Martha Palmer](https://openalex.org/A5017464054) [ORCID](https://orcid.org/0000-0001-9864-6974) · [Semantic Scholar](https://www.semanticscholar.org/author/145755155) · h 57 · 21263 citations · 417 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

The paper presents VerbNet's revised semantic representations, shown on the 37 classes (810 verbs) of change of possession and transfer of information. The old Start/During/End scheme with a generic `path_rel` is replaced by numbered subevents in the style of the Generative Lexicon's dynamic event model, with opposed predicates before and after the change and explicit `cause(e_i, e_j)`. A transfer of possession is: the source has the theme and the recipient does not (e1), the transfer (e2), the recipient has it and the source no longer does (e3), e2 causes e3. Variants say who initiates (an Agent replaces Source in *give*, Recipient in *steal*/*obtain*), two-way exchanges (*sell*, *pay*: two transfers, with `cost`), irrealis for *promise*/*offer*-type future having, and `manner(Illegal)` for *steal*/*rob*. Transfer of information differs in one point: the source keeps the information after telling it, and the hearer's earlier knowledge is left open. A pipeline (VerbNet class tagger, PropBank SRL, role alignment) instantiates these representations from text.

## Ideas

- I1. Turn the semantic predicates already stored in `prag/data/verbnet.tsv` (the frame rows carry `has_possession !has_possession transfer cause …`, but nothing reads them) into derived state facts for the student: after a transfer frame, the recipient has the theme and the source does not; after a motion frame the theme is at the destination and not at the start. Store them as Fact frames linked by `next` and marked as derived (`How` says from which class and frame). Questions «Who had the cheese at the end?» or «Where was the ring after …?» then have a frame to match. Measure with `world knowledge diagnose` the share of «nothing remembered matched» on possession/location questions, and the course test counts.
- I2. Keep the possession/information asymmetry: a say/tell frame leaves the speaker still knowing what was said, a give frame leaves the giver without the thing. A small inference test set from tales (give/lend/steal/tell/teach) with yes/no questions on who has or knows what, as a deterministic gate for I1.
- I3. Use the agent-as-source vs agent-as-recipient distinction to fix role questions: for *steal*, *take*, *buy*, *get* the subject is the one who ends with the thing, for *give*, *sell*, *lend* it is the one who loses it. «From whom did the fox take the cheese?» asks the source oblique. Check on the frame bench and in the to-whom/from-whom questions that docs/mmm-diagnosis.md lists as weak.
- I4. Irrealis for future-having classes (*promise*, *offer*, *owe*): their transfer did not happen yet, so no possession fact is derived. A negative control for I1: «The king promised the miller gold» must not yield «the miller has gold».

## For Mova

[13. Verbs](https://md.mova.elamur.ai/free/en/docs/languages/en/13-verbs/) (verb classes), `30-pragmatics-overview.md` §5.3 (a frame with its pragmatics), `36-discourse-relations.md` §11.4 (story time). Code: `prag/src/vnconv.rs` and `prag/data/verbnet.tsv` (keep predicate arguments and subevent order, not only names), `prag/src/vn.rs`, `prag/src/frames.rs` (derived state frames), `world/src/knowledge.rs`. Measures: diagnosis step shares on possession and location questions, course tests and exams, the inference gate with its negative control.

Topics: [Semantic role labeling](https://md.mova.elamur.ai/free/en/docs/papers/topics/semantic-role-labeling/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/w19-3318](https://doi.org/10.18653/v1/w19-3318)

```
@inproceedings{brown2019verbnet,
  title = {{VerbNet Representations: Subevent Semantics for Transfer Verbs}},
  author = {Brown, Susan Windisch and Bonn, Julia and Gung, James and Zaenen, Annie and Pustejovsky, James and Palmer, Martha},
  booktitle = {Proceedings of the First International Workshop on Designing Meaning Representations},
  year = {2019},
  doi = {10.18653/v1/w19-3318},
  url = {https://doi.org/10.18653/v1/w19-3318}
}
```

- [← previous Focus particles and scalar inferences across humans and language models](https://md.mova.elamur.ai/free/en/docs/papers/brousse-2026-focus-particles-scalar-inferences-across/)
- [next → Revisiting the ISO standard for dialogue act annotation](https://md.mova.elamur.ai/free/en/docs/papers/bunt-2017-revisiting-iso-standard-dialogue-act/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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