---
title: "Universal Dependencies for Croatian — Agić 2015"
description: "The paper addresses dependency parsing for Croatian and Serbian, South Slavic languages that lack annotated resources."
authors: ["Željko Agić", "Nikola Ljubešić"]
year: 2015
venue: "The 5th Workshop on Balto-Slavic Natural Language Processing"
source: "https://aclanthology.org/W15-5301/"
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/papers/agic-2015-universal-dependencies-croatian-that-work/"
---
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# Universal Dependencies for Croatian (that work for Serbian, too)

**Authors:** [Željko Agić](https://md.research.elamur.ai/free/authors/zeljko-agic/), [Nikola Ljubešić](https://md.research.elamur.ai/free/authors/nikola-ljubesic/) · **Year:** 2015 · **Venue:** The 5th Workshop on Balto-Slavic Natural Language Processing · **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/W15-5301/) · [PDF](https://aclanthology.org/W15-5301.pdf) · [OpenAlex](https://openalex.org/W2753789392)

**Citations:** 26 citations (openalex-snapshot · 2026-10-14) · [11](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary

The paper addresses dependency parsing for Croatian and Serbian, South Slavic languages that lack annotated resources. Heterogeneous annotation schemes across treebanks make it hard to compare parsers and to transfer them between languages, whereas UD offers a single cross-lingual format. The authors therefore built Croatian UD: newspaper texts from the SETIMES.HR corpus received new layers of part-of-speech, morphological and syntactic annotation following the UD guidelines. MTE4 tags were manually converted to UPOS and universal morphological features. Four experts annotated the dependency trees from scratch, without automatic conversion. The resource also includes Croatian and Serbian test sets from news and Wikipedia, annotated with the same scheme. Parsers trained on Croatian UD outperformed models using the SETIMES.HR scheme in UAS and LAS. On Serbian texts they are practically as accurate as on Croatian ones. Delexicalized transfer from treebanks of ten European languages is examined separately. On non-unified CoNLL data it yields low scores that do not reflect language relatedness. The work matters because Croatian gained a UD-compatible treebank, and Serbian gained a strong parser without training data of its own.

## Key points

- **Resource.** Croatian UD is annotated on top of the original SETIMES.HR. It comprises 3,557 training and 200 development sentences of newspaper text (3,757 in total), as well as four test sets of 100 sentences each: news and Wikipedia in Croatian and Serbian. The same sentences carry two parallel annotations, SETIMES.HR and UD. The data and the tag mapping table are distributed under a free license (github.com/ffnlp/sethr).
- **Morphology.** 14 of the 17 UPOS tags are used: DET, INTJ and SYM simply did not occur in the texts. Some MTE4 features are absent from the UD specification, so the number of full morphosyntactic tags dropped from 662 to 540. The authors introduced no language-specific extensions, either here or in the syntax.
- **Syntax.** 39 of the 40 universal relations are used (only reparandum is missing), whereas SETIMES.HR has 15 labels. The most frequent relations are nmod (≈17%), punct (≈12.9%) and case (≈9.8%). Following the UD principle, content words become heads, so coordination, subordinate clauses and prepositional phrases are represented differently than in SETIMES.HR. Non-projective sentences make up 7.6% of the UD layer, 10.1% of SETIMES.HR, and about 20% of the PDT-compatible HOBS.
- **Lexicalized parsers.** The experiments use gold POS and features. According to previous studies, LAS with automatic tags is on average 2–3 points lower. The Croatian UD model with UPOS and features achieves an overall UAS of 85.3 / LAS of 79.6, while the equivalent SETIMES.HR model achieves 82.7 / 76.4. On the Serbian test sets this model reaches LAS 81.5 (news) and 77.9 (Wikipedia), on par with 81.5 and 77.3 for Croatian.
- **Cross-lingual transfer.** Delexicalized parsers, whose only feature is CPOS, were trained on treebanks of 10 European languages in their CoNLL 2006–2007 and UD 1.0 versions, i.e. 20 models in total. By UAS, Greek turned out best among the CoNLL sources, while Bulgarian and Czech, which are closer to Croatian and Serbian, ended up considerably lower. Czech, despite the large size of its treebank, came second to last; the authors attribute this to annotation heterogeneity.

*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/shelves/linguistics/)

Topics: [Universal Dependencies](https://md.research.elamur.ai/free/topics/universal-dependencies/) · [Treebanks](https://md.research.elamur.ai/free/topics/treebanks/)

## Cited by

Cited by

11 papers of our library cite it (of the 140673 whose bibliographies we read); 1 of them have a page here, 10 not yet.

- [Universal Dependencies for Arabic](https://md.research.elamur.ai/free/papers/ud-2017-taji-universal-dependencies-arabic/)

## Cite

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

```bibtex
@inproceedings{agic2015universal,
  title = {{Universal Dependencies for Croatian (that work for Serbian, too)}},
  author = {Agić, Željko and Ljubešić, Nikola},
  booktitle = {The 5th Workshop on Balto-Slavic Natural Language Processing},
  year = {2015},
  url = {https://aclanthology.org/W15-5301/}
}
```

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## References

31 references, 5 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Anne Abeillé. 2003. Treebanks: Building and Using Parsed Corpora. Springer. [find](https://scholar.google.com/scholar?q=Anne+Abeille%CC%81%2E+2003%2E+Treebanks%3A+Building+and+Using+Parsed+Corpora%2E+Springer%2E)
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4. Željko Agić, Nikola Ljubešić, and Danijela Merkler. 2013a. Lemmatization and morphosyntactic tagging of Croatian and Serbian. In BSNLP, pages 48–57. [find](https://scholar.google.com/scholar?q=Z%CC%8Celjko+Agic%CC%81%2C+Nikola+Ljubes%CC%8Cic%CC%81%2C+and+Danijela+Merkler%2E+2013a%2E+Lemmatization+and+morphosyntactic+tagging+of+Croatian+and+Serbian%2E+In+BSNLP%2C+pages+48%E2%80%9357%2E)
5. Željko Agić, Danijela Merkler, and Daša Berović. 2013b. Parsing Croatian and Serbian by using Croatian dependency treebanks. In SPMRL, pages 22– 33. [find](https://scholar.google.com/scholar?q=Z%CC%8Celjko+Agic%CC%81%2C+Danijela+Merkler%2C+and+Das%CC%8Ca+Berovic%CC%81%2E+2013b%2E+Parsing+Croatian+and+Serbian+by+using+Croatian+dependency+treebanks%2E+In+SPMRL%2C+pages+22%E2%80%93+33%2E)
6. Željko Agić, Daša Berović, Danijela Merkler, and Marko Tadić. 2014a. Croatian dependency treebank 2.0: New annotation guidelines for improved parsing. In LREC, pages 2313–2319. [find](https://scholar.google.com/scholar?q=Z%CC%8Celjko+Agic%CC%81%2C+Das%CC%8Ca+Berovic%CC%81%2C+Danijela+Merkler%2C+and+Marko+Tadic%CC%81%2E+2014a%2E+Croatian+dependency+treebank+2%2E0%3A+New+annotation+guidelines+for+improved+parsing%2E+In+LREC%2C+pages+2313%E2%80%932319%2E) [our card](https://md.research.elamur.ai/free/papers/agic-2014-croatian-dependency-treebank-2-0/)
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