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# Effective Self-Training for Parsing

**Authors:** [David McClosky](https://md.mova.elamur.ai/free/en/docs/papers/authors/david-mcclosky/), [Eugene Charniak](https://md.mova.elamur.ai/free/en/docs/papers/authors/eugene-charniak/), [Mark Johnson](https://md.mova.elamur.ai/free/en/docs/papers/authors/mark-johnson/) · **Year:** 2006 · **Venue:** Proceedings of the Human Language Technology Conference of the NAACL, Main Conference **Link:** [aclanthology.org/N06-1020](https://aclanthology.org/N06-1020/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**601** citations](https://openalex.org/works?filter=cites:W2163568299) openalex · 2026-10-18[**252** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2006-mcclosky-effective-self-training-parsing/) of the 140673 papers whose bibliographies we read[Proceedings of the Human Language Technology Conference of the NAACL, Main Conference](https://aclanthology.org/volumes/N06-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/N06-1020/)
- [PDF](https://aclanthology.org/N06-1020.pdf)
- [DOI 10.3115/1220835.1220855](https://doi.org/10.3115/1220835.1220855)
- [OpenAlex](https://openalex.org/W2163568299)

**Authors (3)**

1. [David McClosky](https://openalex.org/A5029071304) [ORCID](https://orcid.org/0009-0005-8897-0793) · h 19 · 9378 citations · 50 works
2. [Eugene Charniak](https://openalex.org/A5005380528) h 56 · 13123 citations · 218 works
3. [Mark Johnson](https://openalex.org/A5034461489) [ORCID](https://orcid.org/0000-0003-4809-8441) · h 56 · 23174 citations · 302 works

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

## What it is about

Self-training of parsers was thought to fail because the parser's own errors are amplified. This paper shows that it works when the self-labelled trees come from a two-stage parser and reranker: the 50-best parses of 24 million unlabelled News sentences are reranked, and the reranker's best tree is added to the Wall Street Journal training data, with the two counts merged. Adding the parser's own best trees does not help, but adding the reranker's best trees lifts the first-stage parser from 90.3 to 91.0 F on section 22 at 750k added sentences, and the full system reaches 92.1 F on WSJ, a 12% error reduction. The gain levels off near 91.0 F as more sentences are added.

## Ideas

- I1. en/src/parse.rs training on silver: label the school corpus with the teacher's trees, and separately keep only the trees that `treeagree` agrees with the independent parsers; measure LAS on EWT dev (cv) as the silver set grows, and stop where the curve flattens, as this paper does.
- I2. en/src/ptag.rs and en/src/parse.rs: merge the counts of gold and silver events with a weight (for example 1 and 0.5) instead of equal weights, and measure LAS on EWT dev for both.
- I3. Keep a separate check of whether the silver set gains through the same features as the teacher's (the paper's own hypothesis): measure LAS on EWT dev with silver trees that the Mova parser itself chose, which should show less gain if that is the cause.

## For Mova

The ideas touch the silver corpus in `corpus/` and the agreement rules in `tools/treeagree` (`src/rules.rs`), and the training counts of `en/src/parse.rs`. The chapter that matters for the teacher-student setup is `languages/en/37-register-and-variation`, since the school corpus is not EWT. Measure first I1 on EWT dev, with the cv folds, and keep the EWT test for one run per release.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.3115/1220835.1220855](https://doi.org/10.3115/1220835.1220855)

```
@inproceedings{mcclosky2006effective,
  title = {{Effective Self-Training for Parsing}},
  author = {McClosky, David and Charniak, Eugene and Johnson, Mark},
  booktitle = {Proceedings of the Human Language Technology Conference of the NAACL, Main Conference},
  year = {2006},
  doi = {10.3115/1220835.1220855},
  url = {https://doi.org/10.3115/1220835.1220855}
}
```

- [← previous Probabilistic Disambiguation Models for Wide-Coverage HPSG Parsing](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2005-miyao-probabilistic-disambiguation-models-wide-coverage/)
- [next → Reranking and Self-Training for Parser Adaptation](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2006-mcclosky-reranking-self-training-parser-adaptation/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

20 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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