---
title: "The Persian Dependency Treebank Made Universal — Safari 2022"
description: "Persian lacks large syntactic resources in the Universal Dependencies format."
authors: ["Pegah Safari", "Mohammad Sadegh Rasooli", "Amirsaeid Moloodi", "Alireza Nourian"]
year: 2022
venue: "Proceedings of the Thirteenth Language Resources and Evaluation Conference"
source: "https://aclanthology.org/2022.lrec-1.766/"
licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/safari-2022-persian-dependency-treebank-made-universal/"
---
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# The Persian Dependency Treebank Made Universal

**Authors:** Pegah Safari, Mohammad Sadegh Rasooli, Amirsaeid Moloodi, Alireza Nourian · **Year:** 2022 · **Venue:** Proceedings of the Thirteenth Language Resources and Evaluation Conference · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2022.lrec-1.766/) · [PDF](https://aclanthology.org/2022.lrec-1.766.pdf) · [OpenAlex](https://openalex.org/W7160309767)

**Citations:** 1 citations (openalex-snapshot · 2026-10-14) · [4](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
Persian lacks large syntactic resources in the Universal Dependencies format. Before this work, its only public UD treebank was the news-only Uppsala treebank of about 6K sentences. The authors take the larger, multi-genre Persian Dependency Treebank (PerDT) and convert it to UD with a rule-based pipeline that includes manual handling of special cases. The pipeline has four stages:
1. Re-tokenizing to UD conventions, which means splitting multiword verb forms and pronominal clitics.
2. Mapping PerDT part-of-speech tags to UD tags.
3. Making systematic revisions to the original annotation.
4. Translating PerDT's 43 relations into UD labels using conditional rules, some of which swap heads and dependents.

Proper nouns are recovered with a BERT-based named-entity tagger and then reviewed by hand. Errors that the pipeline flags are also fixed manually. A parser trained on the converted treebank reaches 85.2 LAS. A delexicalized model trained on it transfers to English about 2 LAS points better than one trained on the Uppsala data, which suggests closer agreement with UD guidelines. Persian thus gains a bigger and more consistent resource for parsing and cross-lingual research.

## Key points
- The converted treebank has 29,107 sentences, nearly five times the 5,997 of the Uppsala Persian UD treebank (Seraji et al., 2016). It also covers several genres and a wider vocabulary.
- In supervised parsing, the data gives a labeled attachment F-score of 85.2.
- In delexicalized Persian-to-English parser transfer, it beats the Uppsala treebank by roughly 2% absolute LAS.
- Systematic changes include:
  - reversing the attachment direction of verbal conjunctions;
  - retagging "million"/"billion"-type words as numbers;
  - using surface lemmas for forms of "šodan".
- PROPN tags come from IDEN-tagged phrases plus person and location entities found by a BERT-based Persian NER tagger (Taher et al., 2020). Note that the paper's first author is Mohammad Sadegh Rasooli, with Pegah Safari as an equal-contribution co-author.

*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: [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

4 papers of our library cite it (of the 140673 whose bibliographies we read); 1 of them have a page here, 3 not yet.

- [Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP](https://md.research.elamur.ai/free/en/papers/goot-2021-massive-choice-ample-tasks-machamp/)

## Cite

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

```bibtex
@inproceedings{safari2022persian,
  title = {{The Persian Dependency Treebank Made Universal}},
  author = {Safari, Pegah and Rasooli, Mohammad Sadegh and Moloodi, Amirsaeid and Nourian, Alireza},
  booktitle = {Proceedings of the Thirteenth Language Resources and Evaluation Conference},
  year = {2022},
  doi = {10.63317/38roncj29zvw},
  url = {https://doi.org/10.63317/38roncj29zvw}
}
```

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