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# Probabilistic Disambiguation Models for Wide-Coverage HPSG Parsing

**Authors:** [Yusuke Miyao](https://md.mova.elamur.ai/free/en/docs/papers/authors/yusuke-miyao/) and [Jun'ichi Tsujii](https://md.mova.elamur.ai/free/en/docs/papers/authors/jun-ichi-tsujii/) · **Year:** 2005 · **Venue:** Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05) **Link:** [aclanthology.org/P05-1011](https://aclanthology.org/P05-1011/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**107** citations](https://openalex.org/works?filter=cites:W2121435899) openalex · 2026-10-18[**46** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2005-miyao-probabilistic-disambiguation-models-wide-coverage/) of the 140673 papers whose bibliographies we read[Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05)](https://aclanthology.org/volumes/P05-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/P05-1011/)
- [PDF](https://aclanthology.org/P05-1011.pdf)
- [DOI 10.3115/1219840.1219851](https://doi.org/10.3115/1219840.1219851)
- [OpenAlex](https://openalex.org/W2121435899)

**Authors (2)**

1. [Yusuke Miyao](https://openalex.org/A5004444958) [ORCID](https://orcid.org/0000-0002-0678-3400) · h 35 · 4576 citations · 263 works
2. [Jun'ichi Tsujii](https://openalex.org/A5112241147) h 62 · 16606 citations · 654 works

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

## What it is about

The paper builds log-linear disambiguation models for a wide-coverage HPSG grammar, trained on 20 sections of the Penn Treebank. The main obstacle is estimation cost. The authors compare four ways to reduce it: filtering only, a product model, a reference distribution and a feature function. The reference distribution method is the most accurate and cheapest of them. The model uses 598,326 features. Accuracy is clearly higher on sentences under 10 words, so short-sentence tests overestimate a parser. About one percent of sentences get no parse, which costs recall.

## Ideas

- I1. `en parse-eval`: report LAS in three length bins (under 10 words, 10 to 19, 20 and more) on EWT test. This is a cheap check of the short-sentence effect the paper shows.
- I2. `en/src/parse.rs`: a cheap candidate filter before the perceptron, in the spirit of the reference distribution. It removes candidate heads that a unigram model rules out. Measure LAS and training seconds on EWT dev with `en folds`.
- I3. No-parse count: count EWT test sentences for which the parser returns no tree, and report recall losses on them separately.

## For Mova

The code is `en/src/parse.rs` and the command is `en parse-eval`; the chapter is [20. Syntax: the Universal Dependencies frame](https://md.mova.elamur.ai/free/en/docs/languages/en/20-syntax-overview/). The paper's features are HPSG features, and its data are PTB-based and outside our licence list. Use the length check and the filter idea only, measured on EWT dev and test, with two identical runs.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.3115/1219840.1219851](https://doi.org/10.3115/1219840.1219851)

```
@inproceedings{miyao2005probabilistic,
  title = {{Probabilistic Disambiguation Models for Wide-Coverage HPSG Parsing}},
  author = {Miyao, Yusuke and Tsujii, Jun'ichi},
  booktitle = {Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05)},
  year = {2005},
  doi = {10.3115/1219840.1219851},
  url = {https://doi.org/10.3115/1219840.1219851}
}
```

- [← previous Automatic Interpretation of Noun Compounds Using WordNet Similarity](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2005-kim-automatic-interpretation-noun-compounds-wordnet/)
- [next → Effective Self-Training for Parsing](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2006-mcclosky-effective-self-training-parsing/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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