README.md

metadata

pretty_name: UD Genre Labels 2.18
license: apache-2.0
annotations_creators:
  - machine-generated
language_creators:
  - crowdsourced
multilinguality:
  - multilingual
task_categories:
  - text-classification
tags:
  - universal-dependencies
  - genre-classification
  - sentence-classification
  - multilingual
  - linguistics
  - derived-annotations
  - text
  - tabular
  - datasets
size_categories:
  - 1M<n<10M

UD Genre Labels ud2.18-full-ud-v1

Derived sentence-level genre annotations for the commul/universal_dependencies Universal Dependencies dataset. These labels are produced by the bootstrapping pipeline and are not authoritative gold annotations.

Dataset Description

• Homepage: https://github.com/bot-zen/ud-genre-bootstrap
• Repository: https://github.com/bot-zen/ud-genre-bootstrap
• Source dataset: hf://commul/universal_dependencies
• Paper: https://universaldependencies.org/udw26/papers/41_Paper.pdf
• Point of Contact: appliedlinguisticsdevs@eurac.edu

Dataset Summary

This dataset provides a sentence-level genre layer aligned to the commul/universal_dependencies Parquet release. Each row contains one derived genre label for one UD sentence and can be joined back to the UD source data by (treebank, split, sent_id).

The export is a derived annotation layer, not a replacement for the UD treebanks and not a hand-validated gold genre dataset.

Loading

from datasets import load_dataset

genres = load_dataset(
    "commul/ud_genre",
    revision="2.18",
    split="train",
)

The train split is the single exported split containing all sentence-level genre labels for this artifact.

For immutable provenance, load the artifact tag:

genres = load_dataset(
    "commul/ud_genre",
    revision="artifact/ud2.18-full-ud-v1",
    split="train",
)

Joining With Universal Dependencies

from datasets import load_dataset

genres = load_dataset(
    "commul/ud_genre",
    revision="2.18",
    split="train",
)

ud = load_dataset(
    "commul/universal_dependencies",
    "en_ewt",
    revision="2.18",
    split="train",
)

genre_by_key = {
    (row["treebank"], row["split"], row["sent_id"]): row["genre"]
    for row in genres
    if row["treebank"] == "en_ewt" and row["split"] == "train"
}

first = ud[0]
genre = genre_by_key.get(("en_ewt", "train", first["sent_id"]))

Release Identity

• Artifact ID: ud2.18-full-ud-v1
• HF branches: 2.18
• HF tag: artifact/ud2.18-full-ud-v1
• HF default branch: main
• HF repo: commul/ud_genre
• UD version: 2.18
• Scope: full
• Label schema: ud
• Artifact version: v1
• Source repo: https://github.com/bot-zen/ud-genre-bootstrap
• Source commit: 085d1fd624b44895e15ccd44b48bbc3a7422b7b2
• Source branch: release/v1
• Source tag: source/ud2.18-full-ud-v1
• Config SHA-256: 37c07418cba6e925de19f54dc21935be9ad85176c08e4747b23f8920f9a7e6ea

Release Configuration

• Config: 2.18-community-release
• Run ID: ud-v2.18-community-release-v1
• UD source: hf://commul/universal_dependencies
• UD source revision: 2.18
• Embeddings: intfloat/multilingual-e5-large / mean
• Clustering: gmm
• Reference weighting: sentence_count

Output Columns

• treebank, split, sent_id: primary join key back to UD
• genre: derived sentence label
• confidence: top-1 similarity score for the assigned cluster label
• method: single-genre-treebank, virtual-split, bootstrap-labeled, or bootstrap-inferred
• ud_version, model, pooling, clustering_method, config_name, run_id: compact row-level provenance

Evaluation Framing

• paper_parity is used only for comparison with the original GMM+L paper protocol.
• End-user quality is tracked with sentence-level generalization metrics, which are stricter and more directly relevant for downstream annotation use.
• Known limitation: some paper-era treebank genre inventories are not fully recoverable from current sentence-level metadata subsets.

Release Summary

• Total sentences: 2221815
• Labeled sentences: 2221815
• Genres exported: 19
• Methods exported: bootstrap-inferred, single-genre-treebank, virtual-split

Source Mapping Files

• configs/genre_mappings.json (sha256: 7efe08d31be2514cc3e7b712012b202442134305139ccfb255f6a4039cc79138)
• configs/metadata_patterns.json (sha256: 13aff0b950c8ccb7a3af005cd3140283f02544480837d983133f66889c5f9e17)
• configs/pud-patterns.json (sha256: fe74e16a5136c37e04415eaaee69521d884f23e9ea6f2e76735b23086c5542ae)

Citation

Please cite the UD Workshop paper associated with this dataset: https://universaldependencies.org/udw26/papers/41_Paper.pdf

Contact

Point of Contact: appliedlinguisticsdevs@eurac.edu