---
title: "Cross-Lingual Dependency Parsing with — Tiedemann 2015"
description: "This paper sets up monolingual and cross-lingual dependency parsing baselines for the first release (1.0) of the Universal Dependencies (UD) data set."
authors: ["Jörg Tiedemann"]
year: 2015
venue: "Proceedings of the Third International Conference on Dependency Linguistics (Depling 2015)"
source: "https://aclanthology.org/W15-2137/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/tiedemann-2015-cross-lingual-dependency-parsing-universal/"
---
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# Cross-Lingual Dependency Parsing with Universal Dependencies and Predicted PoS Labels

**Authors:** [Jörg Tiedemann](https://md.research.elamur.ai/free/en/authors/jorg-tiedemann/) · **Year:** 2015 · **Venue:** Proceedings of the Third International Conference on Dependency Linguistics (Depling 2015) · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/W15-2137/) · [PDF](https://aclanthology.org/W15-2137.pdf) · [OpenAlex](https://openalex.org/W2251443950)

**Citations:** 42 citations (openalex-snapshot · 2026-10-14) · [30](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
This paper sets up monolingual and cross-lingual dependency parsing baselines for the first release (1.0) of the Universal Dependencies (UD) data set. It also measures how much results change when parsers receive automatically predicted PoS and morphological tags instead of gold annotation. Ten UD languages are included in the experiments: Czech, English, Finnish, French, German, Hungarian, Irish, Italian, Spanish and Swedish. Parsers were trained with the Mate tools and taggers with Marmot. The study compares three approaches:
- delexicalized model transfer,
- annotation projection over parallel data,
- treebank translation.

With predicted tags, lexicalized monolingual parsers lose only a few LAS points. Delexicalized parsers degrade much more, because they rely entirely on PoS labels. Models trained on noisy projected or translated data also lose accuracy, and their parsing quality correlates strongly with tagger accuracy.

The main takeaway is that evaluating with gold tags overstates real-world performance, especially for delexicalized transfer. Developers should therefore improve tagging before trusting cross-lingual parsers. The paper also finds that current transfer methods work poorly for languages from different families.

## Key points
- **Monolingual baselines:** LAS ranges from 72.73 (Irish, about 0.7k-sentence treebank) to 89.58 (Italian). Removing morphology and lemmas costs Finnish and Hungarian roughly 10 LAS points and Czech about 5.
- **Effect of predicted tags (Marmot):** With full features, monolingual LAS drops about 2–4 points, and 5–7 points for small treebanks (e.g., Hungarian 83.19 → 75.78, Irish 72.73 → 66.74).
- **Delexicalized parsers:** These suffer the most from predicted tags, e.g., Finnish 59.54 → 49.79 and Czech 70.36 → 62.44 LAS.
- **Correlations with tagging:** PoS tagger accuracy correlates strongly with cross-lingual LAS (r = 0.918 for projected models, r = 0.900 for translated models). It correlates negatively with the size of the LAS drop (r ≈ −0.67).
- **Treebank translation:** This approach stays competitive with projection despite low BLEU scores, and BLEU correlates with LAS (r = 0.795). Its lexicalized models lose about 2 LAS points, sometimes more than 4, under predicted tags.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

Topics: [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/) · [Part-of-speech tagging](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/)

## Cited by

Cited by

30 papers of our library cite it (of the 140673 whose bibliographies we read); 6 of them have a page here, 24 not yet.

- [Many Languages, One Parser](https://md.research.elamur.ai/free/en/papers/ammar-2016-many-languages-one-parser/)
- [A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing](https://md.research.elamur.ai/free/en/papers/anderson-2021-falta-de-pan-buenas-son/)
- [Contribution of Linguistic Typology to Universal Dependency Parsing: An Empirical Investigation](https://md.research.elamur.ai/free/en/papers/basirat-2024-contribution-linguistic-typology-universal-dependency/)
- [Universal Dependencies](https://md.research.elamur.ai/free/en/papers/demarneffe-2021-universal-dependencies/)
- [XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/ponti-2020-xcopa-multilingual-dataset-causal-commonsense/)
- [Findings of the VarDial Evaluation Campaign 2017](https://md.research.elamur.ai/free/en/papers/zampieri-2017-findings-vardial-evaluation-campaign/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{tiedemann2015cross,
  title = {{Cross-Lingual Dependency Parsing with Universal Dependencies and Predicted PoS Labels}},
  author = {Tiedemann, Jörg},
  booktitle = {Proceedings of the Third International Conference on Dependency Linguistics (Depling 2015)},
  year = {2015},
  url = {https://aclanthology.org/W15-2137/}
}
```

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## References

26 references, 6 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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