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# Frustratingly Hard Domain Adaptation for Dependency Parsing

**Authors:** Mark Dredze, John Blitzer, Partha Pratim Talukdar, Kuzman Ganchev, João V. Graça, [Fernando Pereira](https://md.mova.elamur.ai/free/en/docs/papers/authors/fernando-pereira/) · **Year:** 2007 · **Venue:** Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL) **Link:** [aclanthology.org/D07-1112](https://aclanthology.org/D07-1112/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only

[**72** citations](https://openalex.org/works?filter=cites:W2152224036) openalex · 2026-10-19[**37** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2007-dredze-frustratingly-hard-domain-adaptation-dependency/) of the 140673 papers whose bibliographies we read[Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)](https://aclanthology.org/volumes/D07-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/D07-1112/)
- [PDF](https://aclanthology.org/D07-1112.pdf)
- [OpenAlex](https://openalex.org/W2152224036)

**Authors (6)**

1. [Mark Dredze](https://openalex.org/A5024437840) [ORCID](https://orcid.org/0000-0002-0422-2474) · [Semantic Scholar](https://www.semanticscholar.org/author/1782853) · h 67 · 23910 citations · 374 works
2. [John Blitzer](https://openalex.org/A5053208168) [Semantic Scholar](https://www.semanticscholar.org/author/2116927) · h 23 · 12793 citations · 49 works
3. [Partha Pratim Talukdar](https://openalex.org/A5033696194) [ORCID](https://orcid.org/0000-0001-8825-589X) · [Semantic Scholar](https://www.semanticscholar.org/author/2408872) · h 47 · 8839 citations · 182 works
4. [Kuzman Ganchev](https://openalex.org/A5081573359) [Semantic Scholar](https://www.semanticscholar.org/author/144422385) · h 24 · 3338 citations · 62 works
5. [João Graça](https://openalex.org/A5110302950) [Semantic Scholar](https://www.semanticscholar.org/author/143836741) · h 2 · 80 citations · 2 works
6. [Fernando Pereira](https://openalex.org/A5044708805) [ORCID](https://orcid.org/0000-0001-6100-947X) · [Semantic Scholar](https://www.semanticscholar.org/author/145366908) · h 74 · 31522 citations · 529 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 authors report their entry to the 2007 CoNLL shared task on domain adaptation, where parsers had to adapt to new domains without labelled target data. Their unlabelled dependency parser, used without any adaptation, placed third of twelve teams, within 1% of the top system. No team improved target-domain accuracy much over that baseline. The error analysis points mainly to differences in annotation guidelines between the treebanks. The result is a warning that adaptation methods cannot repair conventions that differ between the source and the target treebank.

## Ideas

- I1. `en/src/convert.rs` and `en ud-eval`: before mixing treebanks for `en` (EWT, ESLSpok, CHILDES, ATIS, school silver), compare label distributions per treebank and measure the LAS of an EWT-trained `en` on each target before and after the label mapping, two runs each.
- I2. `tools/treeagree check`: count gate violations per treebank and per 1,000 sentences of the school silver, to see which bank's conventions the silver contradicts.
- I3. Do not add domain-adaptation features until I1 shows the guideline gap: compare the LAS loss on ATIS (63.0) and GENTLE (67.9) with the part of the gap that the label mapping explains.

## For Mova

Touches [08. National varieties](https://md.mova.elamur.ai/free/en/docs/languages/en/08-national-varieties/) and [37. Register and variation](https://md.mova.elamur.ai/free/en/docs/languages/en/37-register-and-variation/). The mixed training set (EWT, ESLSpok, CHILDES, ATIS and the school corpus) is exactly the setting where guideline differences decide the result. Measure I1 first, because a conversion fix costs less than any new model.

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.

```
@inproceedings{dredze2007frustratingly,
  title = {{Frustratingly Hard Domain Adaptation for Dependency Parsing}},
  author = {Dredze, Mark and Blitzer, John and Talukdar, Partha Pratim and Ganchev, Kuzman and Graça, João and Pereira, Fernando},
  booktitle = {Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)},
  year = {2007},
  url = {https://aclanthology.org/D07-1112/}
}
```

- [← previous Semantic Composition with (Robust) Minimal Recursion Semantics](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2007-copestake-semantic-composition-robust-minimal-recursion/)
- [next → Part-of-Speech Tagging for Middle English through Alignment and Projection of Parallel Diachronic Texts](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2007-moon-part-speech-tagging-middle-english/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

13 references, 3 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Shai Ben-David, John Blitzer, Koby Crammer, and Fernando Pereira. 2006. Analysis of representations for domain adaptation. In NIPS. [find](https://scholar.google.com/scholar?q=Shai+Ben%2DDavid%2C+John+Blitzer%2C+Koby+Crammer%2C+and+Fernando+Pereira%2E+2006%2E+Analysis+of+representations+for+domain+adaptation%2E+In+NIPS%2E)
2. Leo Breiman. 1996. Bagging predictors. Learning, 24(2):123–140. [find](https://scholar.google.com/scholar?q=Leo+Breiman%2E+1996%2E+Bagging+predictors%2E+Learning%2C+24%282%29%3A123%E2%80%93140%2E) [our card](https://md.mova.elamur.ai/free/en/docs/papers/breiman-1996-bagging-predictors/)
3. Machine R. Brown. 1973. A First Language: The Early Stages. Harvard University Press. [find](https://scholar.google.com/scholar?q=Machine+R%2E+Brown%2E+1973%2E+A+First+Language%3A+The+Early+Stages%2E+Harvard+University+Press%2E)
4. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, and Yoram Singer. 2006. Online passive-aggressive algorithms. Journal of Machine Learning Research, 7:551–585, Mar. [find](https://scholar.google.com/scholar?q=Koby+Crammer%2C+Ofer+Dekel%2C+Joseph+Keshet%2C+Shai+Shalev%2DShwartz%2C+and+Yoram+Singer%2E+2006%2E+Online+passive%2Daggressive+algorithms%2E+Journal+of+Machine+Learning+Research%2C+7%3A551%E2%80%93585%2C+Mar%2E)
5. R. Johansson and P. Nugues. 2007. Extended constituent-to-dependency conversion for English. In Proc. of the 16th Nordic Conference on Computational Linguistics (NODALIDA). [find](https://scholar.google.com/scholar?q=R%2E+Johansson+and+P%2E+Nugues%2E+2007%2E+Extended+constituent%2Dto%2Ddependency+conversion+for+English%2E+In+Proc%2E+of+the+16th+Nordic+Conference+on+Computational+Linguistics+%28NODALIDA%29%2E) [our card](https://md.mova.elamur.ai/free/en/docs/papers/map-2007-johansson-extended-constituent-dependency-conversion-english/)
6. Sandra Kübler. 2006. How do treebank annotation schemes influence parsing results? or how not to compare apples and oranges. In RANLP. [find](https://scholar.google.com/scholar?q=Sandra+Ku%CC%88bler%2E+2006%2E+How+do+treebank+annotation+schemes+influence+parsing+results%3F+or+how+not+to+compare+apples+and+oranges%2E+In+RANLP%2E)
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8. B. MacWhinney. 2000. The CHILDES Project: Tools for Analyzing Talk. Lawrence Erlbaum. [find](https://scholar.google.com/scholar?q=B%2E+MacWhinney%2E+2000%2E+The+CHILDES+Project%3A+Tools+for+Analyzing+Talk%2E+Lawrence+Erlbaum%2E)
9. M. Marcus, B. Santorini, and M. Marcinkiewicz. 1993. Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, 19(2):313–330. [find](https://scholar.google.com/scholar?q=M%2E+Marcus%2C+B%2E+Santorini%2C+and+M%2E+Marcinkiewicz%2E+1993%2E+Building+a+large+annotated+corpus+of+English%3A+the+Penn+Treebank%2E+Computational+Linguistics%2C+19%282%29%3A313%E2%80%93330%2E) [our card](https://md.mova.elamur.ai/free/en/docs/papers/bank-1993-marcus-building-large-annotated-corpus-english/)
10. Ryan McDonald, Kevin Lerman, and Fernando Pereira. 2006. Multilingual dependency parsing with a two-stage discriminative parser. In Conference on Natural Language Learning (CoNLL). [find](https://scholar.google.com/scholar?q=Ryan+McDonald%2C+Kevin+Lerman%2C+and+Fernando+Pereira%2E+2006%2E+Multilingual+dependency+parsing+with+a+two%2Dstage+discriminative+parser%2E+In+Conference+on+Natural+Language+Learning+%28CoNLL%29%2E)
11. J. Nivre, J. Hall, S. Kübler, R. McDonald, J. Nilsson, S. Riedel, and D. Yuret. 2007. [find](https://scholar.google.com/scholar?q=J%2E+Nivre%2C+J%2E+Hall%2C+S%2E+Ku%CC%88bler%2C+R%2E+McDonald%2C+J%2E+Nilsson%2C+S%2E+Riedel%2C+and+D%2E+Yuret%2E+2007%2E)
12. The CoNLL 2007 shared task on dependency parsing. In Proc. of the CoNLL 2007 Shared Task. Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). [find](https://scholar.google.com/scholar?q=The+CoNLL+2007+shared+task+on+dependency+parsing%2E+In+Proc%2E+of+the+CoNLL+2007+Shared+Task%2E+Joint+Conf%2E+on+Empirical+Methods+in+Natural+Language+Processing+and+Computational+Natural+Language+Learning+%28E)
13. Lawrence Saul and Fernando Pereira. 1997. Aggregate and mixed-order markov models for statistical language modeling. In EMNLP. [find](https://scholar.google.com/scholar?q=Lawrence+Saul+and+Fernando+Pereira%2E+1997%2E+Aggregate+and+mixed%2Dorder+markov+models+for+statistical+language+modeling%2E+In+EMNLP%2E)