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# CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

**Authors:** [Daniel Zeman](https://md.mova.elamur.ai/free/en/docs/papers/authors/daniel-zeman/), [Jan Hajič](https://md.mova.elamur.ai/free/en/docs/papers/authors/jan-hajic/), [Martin Popel](https://md.mova.elamur.ai/free/en/docs/papers/authors/martin-popel/) et al. · **Year:** 2018 · **Venue:** Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies **Link:** [aclanthology.org/K18-2001](https://aclanthology.org/K18-2001/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**61** citations](https://openalex.org/works?filter=cites:W2917956622) openalex · 2026-10-18[**254** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2018-zeman-conll-2018-shared-task-multilingual/) of the 140673 papers whose bibliographies we read[Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies](https://aclanthology.org/volumes/K18-2/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/K18-2001/)
- [PDF](https://aclanthology.org/K18-2001.pdf)
- [DOI 10.18653/v1/k18-2001](https://doi.org/10.18653/v1/k18-2001)
- [OpenAlex](https://openalex.org/W2917956622)

**Authors (8)**

1. [Daniel Zeman](https://openalex.org/A5061392927) [ORCID](https://orcid.org/0000-0002-5791-6568) · h 28 · 4506 citations · 176 works
2. [Jan Hajič](https://openalex.org/A5102738283) [ORCID](https://orcid.org/0000-0002-3503-7730) · h 39 · 8500 citations · 313 works
3. [Martin Popel](https://openalex.org/A5083887502) [ORCID](https://orcid.org/0000-0002-3628-8419) · h 21 · 2689 citations · 110 works
4. [Martin Potthast](https://openalex.org/A5083712311) [ORCID](https://orcid.org/0000-0003-2451-0665) · h 45 · 9009 citations · 559 works
5. [Milan Straka](https://openalex.org/A5060081515) [ORCID](https://orcid.org/0000-0003-3295-5576) · h 22 · 3117 citations · 294 works
6. [Filip Ginter](https://openalex.org/A5019929457) [ORCID](https://orcid.org/0000-0002-5484-6103) · h 36 · 7686 citations · 203 works
7. [Joakim Nivre](https://openalex.org/A5077063699) h 60 · 16290 citations · 335 works
8. [Slav Petrov](https://openalex.org/A5062886906) [ORCID](https://orcid.org/0000-0002-5505-4861) · h 39 · 16324 citations · 107 works

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

## What it is about

This overview describes the second CoNLL shared task on parsing raw text into UD. Systems start from raw text, with no gold segmentation or tags, and are scored on 82 test treebanks, with macro-averaged LAS and two new metrics, MLAS (labels plus morphological features) and BLEX (lemmas plus labels). Eight new languages are added and the training data is UD 2.2 with large crawled raw text. The best system, HIT-SCIR, reaches 75.84 macro LAS; the UDPipe 1.2 baseline reaches 65.80, and 17 of the 25 systems beat it. The baseline is weaker than in 2017, and the paper notes that the ranking changes under MLAS and BLEX, where the baseline does better on lemmas. Most systems use pretrained word embeddings, and many use the Stanford graph-based parser or a reimplementation of it.

## Ideas

- I1. `en parse-eval` and `en ud-eval`: report MLAS and BLEX next to LAS for EWT test; metric: the three numbers per release (current EWT: LAS 80.24, MLAS 70.75), so that morphology and lemma errors are not hidden by LAS.
- I2. `en/src/tok.rs` plus `en/src/ptag.rs` plus `en/src/parse.rs`: run the English raw-text protocol end to end (predicted segmentation and tags, no gold), and report the LAS loss against gold tokens; the paper's systems lose several points here, and Mova reports gold numbers only.
- I3. Score each test file separately and report the macro average over the English treebanks (EWT, GUM, ATIS, PUD, GENTLE), as the shared task does; GUM and GENTLE are test only.

## For Mova

The chapter is [20. Syntax: the Universal Dependencies frame](https://md.mova.elamur.ai/free/en/docs/languages/en/20-syntax-overview/). The code is `en/src/udreg.rs` (the registry gate), `en/src/morph.rs` (lemma accuracy for BLEX) and `tools/parsecmp` for side-by-side outputs. The shared task is a measurement frame, not a method, so the useful outcome is a reporting change: add MLAS, BLEX and the raw-text LAS to the measurements.

Topics: [Universal Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/topics/universal-dependencies/) · [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/k18-2001](https://doi.org/10.18653/v1/k18-2001)

```
@inproceedings{zeman2018conll,
  title = {{CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies}},
  author = {Zeman, Daniel and Hajič, Jan and Popel, Martin and Potthast, Martin and Straka, Milan and Ginter, Filip and Nivre, Joakim and Petrov, Slav},
  booktitle = {Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies},
  year = {2018},
  doi = {10.18653/v1/k18-2001},
  url = {https://doi.org/10.18653/v1/k18-2001}
}
```

- [← previous Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning](https://md.mova.elamur.ai/free/en/docs/papers/ud-2018-yu-approximate-dynamic-oracle-dependency-parsing/)
- [next → Towards an adequate account of parataxis in Universal Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/ud-2019-ahrenberg-adequate-account-parataxis-universal-dependencies/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

39 references, 30 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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