AfriSUD

AfriSUD is a collection of manually annotated treebanks for African languages following the Surface-Syntactic Universal Dependencies (SUD) framework. The dataset is intended to support research on dependency parsing, multilingual and cross-lingual NLP, and language technologies for low-resource African languages.

AfriSUD is introduced in our paper, AfriSUD: A Dependency Treebank Collection for Evaluating Models on African Languages.

Loading the Dataset

Each language is available as a separate configuration.

For example, Hausa can be loaded with:

from datasets import load_dataset

dataset = load_dataset(
    "Lugha-Models/AfriSUD",
    "hau"
)

Languages

AfriSUD currently includes treebank data for eight African languages:

Code	Language
hau	Hausa
kin	Kinyarwanda
nyn	Runyankore
pcm	Nigerian Pidgin
swa	Kiswahili
wol	Wolof
xho	isiXhosa
yor	Yorùbá

Dataset Format

The canonical release is provided in CoNLL-U format, with Parquet versions included for convenient access through the Hugging Face Dataset Viewer.

Annotation Guidelines

The annotation guidelines used to create AfriSUD are available here:

📄 SUD Annotation Guidelines

Paper

For more details about AfriSUD, including the annotation process, dataset construction, and evaluation experiments, see our paper:

AfriSUD: A Dependency Treebank Collection for Evaluating Models on African Languages

📄 Paper on arXiv

Citation

If you use AfriSUD in your research, please cite:

@inproceedings{buzaaba-etal-2026-afrisud,
    title = "{A}fri{SUD}: A Dependency Treebank Collection for Evaluating Models on {A}frican Languages",
    author = "Buzaaba, Happy  and Dione, Cheikh Mouhamadou Bamba  and Adelani, David Ifeoluwa  and Kahane, Sylvain  and Guillaume, Bruno  and Gerdes, Kim  and Muhammad,
      Shamsuddeen Hassan  and Guan, Kevin  and Aremu, Anuoluwapo  and Etori, Naome A  and Inyang, Utitofon  and Nabende, Peter  and Bamutura, David Sabiiti  and Bukula, Andiswa  and
      Akinade, Idris  and Uchechukwu, Chinedu  and Mabuya, Rooweither  and Fellbaum, Christiane",
    editor = "Lee, Hung-Yi  and Dev, Sunipa  and Li, Junyi Jessy  and Elliott, Desmond",
    booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
    month = oct,
    year = "2026",
    address = "Budapest, Hungary",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.emnlp-main.1896/",
    doi = "10.18653/2026.emnlp-main.1896",
    pages = "43227--43248",
    ISBN = "979-8-89176-459-0",
    abstract = "Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP.
                We aim to bridge this gap by introducing \textbf{AfriSUD}, the first multilingual collection of syntactically annotated treebanks for nine diverse African languages
                spanning major language families and regions across Sub-Saharan Africa. Using the Surface-Syntactic Universal Dependencies (SUD) framework, our community-led effort provides
                high-quality, native-speaker-verified data that capture typological key features such as agglutination and tone. We evaluate a range of models on AfriSUD for part-of-speech tagging and
                dependency parsing, including non-transformer baselines, multilingual pretrained encoders, and LLMs. Our results reveal a significant syntax gap, where models still show clear limitations
                across the nine languages, suggesting that existing architectures may not fully capture the structural diversity of African-language syntax."
}

Acknowledgments

This work was supported by Princeton Language and Intelligence (PLI) seed grant.