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# Verb Phrase Ellipsis Resolution Using Discriminative and Margin-Infused Algorithms

**Authors:** Kian Kenyon-Dean, [Jackie Chi Kit Cheung](https://md.mova.elamur.ai/free/en/docs/papers/authors/jackie-chi-kit-cheung/) and Doina Precup · **Year:** 2016 · **Venue:** Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP 2016) **Link:** [aclanthology.org/D16-1179](https://aclanthology.org/D16-1179/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**17** citations](https://openalex.org/works?filter=cites:W2565926555) openalex · 2026-10-19[**7** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2016-dean-verb-phrase-ellipsis-resolution-discriminative/) of the 140673 papers whose bibliographies we read[Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing](https://aclanthology.org/volumes/D16-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/D16-1179/)
- [PDF](https://aclanthology.org/D16-1179.pdf)
- [DOI 10.18653/v1/d16-1179](https://doi.org/10.18653/v1/d16-1179)
- [OpenAlex](https://openalex.org/W2565926555)

**Authors (3)**

1. Kian Kenyon-Dean
2. [Jackie Chi Kit Cheung](https://openalex.org/A5050801868) [Semantic Scholar](https://www.semanticscholar.org/author/3159752) · h 28 · 2391 citations · 149 works
3. [Doina Precup](https://openalex.org/A5127784613) [Semantic Scholar](https://www.semanticscholar.org/author/144368601) · h 5 · 218 citations · 8 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 resolves VP ellipsis (VPE) in two steps. The first step decides whether a word triggers VPE. The second picks the antecedent clause and its exact boundaries. Both steps are supervised machine learning over features from an automatically parsed corpus, the Bos and Spenader VPE data on the Wall Street Journal. Trigger detection uses a logistic regression classifier with separate handling of six trigger forms, including modals, the verbs be, do and have, and to-VPE. Detection accuracy rises from 69.52% to 80.78%, an improvement of over 11%. For antecedent identification, a margin-infused (MIRA) ranker beats a simple baseline. The chosen strategy gets 92% of gold antecedents right on the validation set by head match.

## Ideas

- I1. `en/src/expert.rs`: write one deterministic rule per trigger form (modal, be, do, have, to) and report its accuracy next to the logistic model. If the rules match the model on a test set we may use, the model is not needed for detection.
- I2. c-command check: keep only antecedent heads that c-command the trigger in the UD tree, approximated by the path from the head to the trigger. Measure head accuracy on the test set with and without the check. The paper finds c-command important for both steps.
- I3. Stage-separated report: report detection accuracy, antecedent accuracy and end-to-end resolution in separate lines, and the ceiling from gold triggers, as the paper does. This shows which step limits the system before any tuning.

## For Mova

The code is `en/src/expert.rs` and `en/src/ctx.rs`. The chapter is [29. Ellipsis, word order and information structure](https://md.mova.elamur.ai/free/en/docs/languages/en/29-ellipsis-word-order-information-structure/). The Wall Street Journal data is Penn Treebank data, which is licensed, so the paper's numbers are not Mova numbers and the data is not built in. Measure first on a VPE test set whose licence allows testing, with the rule and model comparison.

Topics: [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/d16-1179](https://doi.org/10.18653/v1/d16-1179)

```
@inproceedings{kenyondean2016verb,
  title = {{Verb Phrase Ellipsis Resolution Using Discriminative and Margin-Infused Algorithms}},
  author = {Kenyon-Dean, Kian and Cheung, Jackie Chi Kit and Precup, Doina},
  booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
  year = {2016},
  doi = {10.18653/v1/d16-1179},
  url = {https://doi.org/10.18653/v1/d16-1179}
}
```

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