xqasem 0.1.0

Cross-lingual QASem parser for predicate-centered question-answer structures.

XQASem

XQASem is a small Python package for extracting predicate-centered question-answer structures from text. It currently includes presets for French, Russian, and Hebrew models hosted on Hugging Face.

The repository contains code only. Model weights should stay on Hugging Face rather than in Git.

This package accompanies the paper Effective QA-Driven Annotation of Predicate-Argument Relations Across Languages.

Installation

After the package is published to PyPI:

pip install xqasem

Install the spaCy pipelines you plan to use:

python -m spacy download fr_core_news_md
python -m spacy download ru_core_news_sm

Hebrew uses spacy-stanza; on first use, Stanza may need to download its Hebrew resources.

Installation from source

git clone https://github.com/JohnnieDavidov/xqasem.git
cd xqasem
pip install -e .

Basic Usage

from xqasem import XQasemParser

parser = XQasemParser.from_language("fr")

sentences = [
    "Les experts ont souligné que le nouvel algorithme accélère considérablement le traitement des requêtes complexes."
]

df = parser(sentences)

print(df)

Example output:

sentence	predicate	predicate_type	question	answer
Les experts ont souligné que le nouvel algorithme accélère considérablement le traitement des requêtes complexes.	souligné	verb	qui a souligné quelque chose?	Les experts
Les experts ont souligné que le nouvel algorithme accélère considérablement le traitement des requêtes complexes.	accélère	verb	qu'est-ce qui accélère quelque chose?	le nouvel algorithme
Les experts ont souligné que le nouvel algorithme accélère considérablement le traitement des requêtes complexes.	accélère	verb	qu'est-ce que quelque chose accélère?	le traitement des requêtes complexes

The built-in language presets are:

parser_fr = XQasemParser.from_language("fr")
parser_ru = XQasemParser.from_language("ru")
parser_he = XQasemParser.from_language("he")

You can also load an explicit Hugging Face model:

parser = XQasemParser.from_pretrained(
    "YonatanDavidov/qasem-fr-claire-lora",
    spacy_lang="fr_core_news_md",
    is_adapter=True,
)

Command Line

After installing the package:

xqasem-parse --lang fr --output outputs/fr.csv "Les experts ont souligné que le nouvel algorithme accélère le traitement."

You can also run the script directly:

python scripts/run_parser.py --lang fr --output outputs/fr.csv

Model Presets

Language	Model	spaCy pipeline
French	YonatanDavidov/qasem-fr-claire-lora	fr_core_news_md
Russian	YonatanDavidov/qasem-ru-sambalingo-lora	ru_core_news_sm
Hebrew	YonatanDavidov/qasem-he-dictalm2-lora	he via spacy-stanza
Hebrew full model	YonatanDavidov/qasem-he-dictalm2-full	he via spacy-stanza

Smoke Test

To check that the installed package, spaCy pipelines, model loading, and output writing work end to end, run:

python scripts/smoke_test_languages.py --langs fr ru he --output-dir outputs/smoke

For a faster sanity check on one language:

python scripts/smoke_test_languages.py --langs fr --max-items 2

The smoke test writes one CSV per language and prints the number of rows produced. It is intended for local validation and is not run as part of the lightweight unit tests.

Development

pip install -e ".[dev]"
pytest

Large model files, checkpoints, generated outputs, and local experiment directories are intentionally ignored by .gitignore.

Publishing to PyPI

The public package name is xqasem. After updating the version in pyproject.toml and xqasem/__init__.py, build and publish with:

python -m pip install --upgrade build twine
python -m build
python -m twine upload dist/*

After the first PyPI release, users can install the package with:

pip install xqasem

Citation

If you use this code or the released models, please cite:

@inproceedings{davidov-etal-2026-effective,
    title = "Effective {QA}-Driven Annotation of Predicate{--}Argument Relations Across Languages",
    author = "Davidov, Jonathan  and
      Slobodkin, Aviv  and
      Klein, Shmuel Tomi  and
      Tsarfaty, Reut  and
      Dagan, Ido  and
      Klein, Ayal",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\\'i}s",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.eacl-long.112/",
    doi = "10.18653/v1/2026.eacl-long.112",
    pages = "2484--2502",
    ISBN = "979-8-89176-380-7"
}

Acknowledgments

• Ayal Klein
• Paul Roit

This implementation builds on ideas and code structure from Paul Roit's qasem_parser, which provides the original English QA-Sem parsing framework that inspired this multilingual extension.