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# Mind the Gap: Data Enrichment in Dependency Parsing of Elliptical Constructions

**Authors:** [Kira Droganova](https://md.mova.elamur.ai/free/en/docs/papers/authors/kira-droganova/), [Filip Ginter](https://md.mova.elamur.ai/free/en/docs/papers/authors/filip-ginter/), [Jenna Kanerva](https://md.mova.elamur.ai/free/en/docs/papers/authors/jenna-kanerva/), [Daniel Zeman](https://md.mova.elamur.ai/free/en/docs/papers/authors/daniel-zeman/) · **Year:** 2018 · **Venue:** Proceedings of the Second Workshop on Universal Dependencies (UDW 2018) **Link:** [aclanthology.org/W18-6006](https://aclanthology.org/W18-6006/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**6** citations](https://openalex.org/works?filter=cites:W2911959277) openalex · 2026-10-19[**9** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2018-droganova-mind-gap-data-enrichment-dependency/) of the 140673 papers whose bibliographies we read[Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)](https://aclanthology.org/volumes/W18-60/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/W18-6006/)
- [PDF](https://aclanthology.org/W18-6006.pdf)
- [DOI 10.18653/v1/w18-6006](https://doi.org/10.18653/v1/w18-6006)
- [OpenAlex](https://openalex.org/W2911959277)

**Authors (4)**

1. [Kira Droganova](https://openalex.org/A5060911811) [ORCID](https://orcid.org/0000-0002-5230-0975) · [Semantic Scholar](https://www.semanticscholar.org/author/22341186) · h 6 · 493 citations · 31 works
2. [Filip Ginter](https://openalex.org/A5019929457) [ORCID](https://orcid.org/0000-0002-5484-6103) · [Semantic Scholar](https://www.semanticscholar.org/author/1694491) · h 36 · 7686 citations · 203 works
3. [Jenna Kanerva](https://openalex.org/A5048932608) [ORCID](https://orcid.org/0000-0003-4580-5366) · [Semantic Scholar](https://www.semanticscholar.org/author/1776599) · h 15 · 1197 citations · 74 works
4. [Daniel Zeman](https://openalex.org/A5061392927) [ORCID](https://orcid.org/0000-0002-5791-6568) · [Semantic Scholar](https://www.semanticscholar.org/author/1771298) · h 28 · 4506 citations · 176 works

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

## What it is about

Gapping (for example "Mary won gold and Peter bronze") is rare in treebanks, so parsers learn it poorly: the orphan relation has almost no training examples. The authors enrich training data in two ways: they parse web-crawl sentences with two parsers and keep only the trees on which both agree, sampled so that tree length and relation diversity follow the treebank; and they add artificial gapping sentences made by deleting a coordinated verb. Five languages are tested with the CoNLL 2017 winning parser. For English, adding the artificial sentences and 15% of the filtered web data raises the orphan F-score from 3.4 to 36.2, while overall LAS stays at about 87 (86.94 to 87.07). Improvements in overall LAS for the other languages are small, and the Czech treebank does not benefit.

## Ideas

- I1. `en/src/parse.rs`: measure orphan precision, recall and F on the English gapping test (the 466 sentences of Schuster et al. 2018 plus the two orphan relations of EWT test), and LAS on EWT test as the guard; test only, if the licence of that set does not allow training.
- I2. `annot` crate and `gparse`: label raw text with the `en` perceptron and `gparse`, and keep only sentences on which both agree, as a silver source for orphan examples; metric: orphan F on the test set above, LAS on EWT test, run twice to check determinism.
- I3. Stratified sampling of silver trees by (tokens, unique relation types per token): compare with random sampling at equal token count on EWT dev with `en parse-eval`; the paper finds the stratified sample better.
- I4. Artificial gapping by deleting the verb of a coordinated clause, filtered by the grammar rules in `en/seeds/verbal` rather than by hand; metric: share of artificial sentences a human judges grammatical on 50 samples.

## For Mova

This is [29. Ellipsis, word order and information structure](https://md.mova.elamur.ai/free/en/docs/languages/en/29-ellipsis-word-order-information-structure/) and `24-coordination-subordination.md`. Code: `en/src/parse.rs` for the gate, `annot` for the silver trees, and `en/src/ctx.rs` if orphan frames are to enter `world`. The idea that sentences both parsers agree on are safe is an example of "examples are not truth": measure the error rate of the agreed set before using it.

Topics: [Dependency parsing](https://md.mova.elamur.ai/free/en/docs/papers/topics/dependency-parsing/) · [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/w18-6006](https://doi.org/10.18653/v1/w18-6006)

```
@inproceedings{droganova2018mind,
  title = {{Mind the Gap: Data Enrichment in Dependency Parsing of Elliptical Constructions}},
  author = {Droganova, Kira and Ginter, Filip and Kanerva, Jenna and Zeman, Daniel},
  booktitle = {Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)},
  year = {2018},
  doi = {10.18653/v1/w18-6006},
  url = {https://doi.org/10.18653/v1/w18-6006}
}
```

- [← previous Twitter Universal Dependency Parsing for African-American and Mainstream American English](https://md.mova.elamur.ai/free/en/docs/papers/ud-2018-blodgett-twitter-universal-dependency-parsing-african/)
- [next → The 2018 Shared Task on Extrinsic Parser Evaluation: On the Downstream Utility of English Universal Dependency Parsers](https://md.mova.elamur.ai/free/en/docs/papers/ud-2018-fares-2018-shared-task-extrinsic-parser/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

11 references, 4 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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6. Kenji Sagae and Junichi Tsujii. 2007. Dependency parsing and domain adaptation with LR models and parser ensembles. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). [find](https://scholar.google.com/scholar?q=Kenji+Sagae+and+Junichi+Tsujii%2E+2007%2E+Dependency+parsing+and+domain+adaptation+with+LR+models+and+parser+ensembles%2E+In+Proceedings+of+the+2007+Joint+Conference+on+Empirical+Methods+in+Natural+Language)
7. Sebastian Schuster, Joakim Nivre, and Christopher D. Manning. 2018. Sentences with Gapping: Parsing and Reconstructing Elided Predicates. In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2018). [find](https://scholar.google.com/scholar?q=Sebastian+Schuster%2C+Joakim+Nivre%2C+and+Christopher+D%2E+Manning%2E+2018%2E+Sentences+with+Gapping%3A+Parsing+and+Reconstructing+Elided+Predicates%2E+In+Proceedings+of+the+16th+Annual+Conference+of+the+North+Amer) [our card](https://md.mova.elamur.ai/free/en/docs/papers/ud-2018-schuster-sentences-gapping-parsing-reconstructing-elided/)
8. Anders Søgaard and Christian Rishøj. 2010. Semi-supervised dependency parsing using generalized tri-training. In Proceedings of the 23rd International Conference on Computational Linguistics, pages 1065–1073. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Anders+S%C3%B8gaard+and+Christian+Rish%C3%B8j%2E+2010%2E+Semi%2Dsupervised+dependency+parsing+using+generalized+tri%2Dtraining%2E+In+Proceedings+of+the+23rd+International+Conference+on+Computational+Linguistics%2C+pages+10)
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