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# Verb Phrase Ellipsis detection using Automatically Parsed Text

**Authors:** [Leif Arda Nielsen](https://md.mova.elamur.ai/free/en/docs/papers/authors/leif-arda-nielsen/) · **Year:** 2004 · **Venue:** COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics **Link:** [aclanthology.org/C04-1157](https://aclanthology.org/C04-1157/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**23** citations](https://openalex.org/works?filter=cites:W2141184766) openalex · 2026-10-18[**12** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2004-nielsen-verb-phrase-ellipsis-detection-automatically/) of the 140673 papers whose bibliographies we read[COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics](https://aclanthology.org/volumes/C04-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/C04-1157/)
- [PDF](https://aclanthology.org/C04-1157.pdf)
- [DOI 10.3115/1220355.1220512](https://doi.org/10.3115/1220355.1220512)
- [OpenAlex](https://openalex.org/W2141184766)

**Authors (1)**

1. [Nielsen, Leif Arda](https://openalex.org/A5077271519) h 4 · 58 citations · 9 works

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

## What it is about

Nielsen builds a detector for VP ellipsis, the first stage of a full resolver. It works on free text that has been parsed automatically. Three learners are compared: memory-based learning and two maximum-entropy models (GIS and L-BFGS). The detector reaches 72% F1 on a mixed corpus. Earlier work by Hardt reports 48% F1 for the same task. Using the Penn Treebank with empty-category information, the empty VP feature alone reaches 70% F1, and the full system 82%. Re-parsing the treebank gives 67%, and parsing parts of the BNC gives 71%. Combining the two gives 71–72%. The empty VP feature is the most informative one, and the drop from gold to parsed input is the main loss.

## Ideas

- I1. `en/src/expert.rs`: a rule detector for the trigger. An auxiliary or modal with no verbal complement (no xcomp, ccomp or conjoined verb in the UD tree) is a candidate VPE site. Measure precision and recall on any VPE-annotated set whose licence allows testing.
- I2. Learned detector with the same features: a per-token binary classifier on `en` features (aux token, tag, next punctuation, sentence position), trained on the training part and scored with `en folds`. Report F1 by feature group, so that each group can be judged alone.
- I3. Gold against parsed input: report detection F1 on gold trees and on `en` trees for the same sentences. The gap between the two is the figure that tells the operator how much parser error costs the detector.

## For Mova

The code is `en/src/expert.rs` and `en/src/ptag.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 BNC is NC, so any BNC material is for measurement only. Measure first: the rule detector against the gold-tree and parsed-tree gap on a test set we are allowed to use.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.3115/1220355.1220512](https://doi.org/10.3115/1220355.1220512)

```
@inproceedings{nielsen2004verb,
  title = {{Verb Phrase Ellipsis detection using Automatically Parsed Text}},
  author = {Nielsen, Leif Arda},
  booktitle = {COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics},
  year = {2004},
  doi = {10.3115/1220355.1220512},
  url = {https://doi.org/10.3115/1220355.1220512}
}
```

- [← previous Robust VPE Detection using Automatically Parsed Text](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2004-nielsen-robust-vpe-detection-automatically-parsed/)
- [next → Deterministic Dependency Parsing of English Text](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2004-nivre-deterministic-dependency-parsing-english-text/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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