Dataset Card for TajikMCQA
Dataset Details
Dataset Description
TajikMCQA is a Multiple Choice Question Answering (MCQA) dataset in the Tajik language, containing 18,016 questions across 573 subjects spanning diverse knowledge domains. The dataset is intended for training and evaluating MCQA models for low-resource languages, with particular focus on Central Asian linguistic diversity.
- Curated by: TajikNLPWorld
- Language(s) (NLP): Tajik (
tg) - License:
other– see Licensing & Legal Notice below.
Licensing & Legal Notice
This dataset follows the practice established by large web‑crawled corpora such as HPLT and OSCAR:
- Original question texts (questions, answer options) remain the property of their respective authors and educators. They are not owned by the TajikNLPWorld team and are not covered by the CC BY‑SA 4.0 license.
- The structured compilation, metadata, annotations (correct answer labels), and packaging created by TajikNLPWorld are released under the CC BY‑SA 4.0 license.
- Users are solely responsible for ensuring their use of the underlying content complies with applicable copyright law. For commercial use of verbatim excerpts, permission from the original copyright holders may be required.
- A notice‑and‑takedown procedure is in place: rights holders can request removal of specific content by contacting the dataset maintainers (see Dataset Card Contact). We commit to responding within 14 business days and removing disputed content in the next release.
Dataset Sources
Uses
Direct Use
The dataset is intended for:
- Training and evaluating multiple-choice question answering models for the Tajik language.
- Benchmarking low-resource language models on knowledge-intensive tasks.
- Research on cross-lingual transfer and domain adaptation for Central Asian languages.
- Educational applications such as automated quiz generation or assessment tools.
Out-of-Scope Use
The dataset should not be used:
- As a source of truth for critical decisions (e.g., medical, legal, or safety-critical systems).
- For any purpose that violates the original copyright of the question texts (see Licensing & Legal Notice).
- To discriminate against or misrepresent any group of people.
Dataset Structure
The dataset consists of a single split (train) with 18,016 examples. Each example is a multiple-choice question with exactly four answer options and one correct answer.
Data Fields
| Field | Type | Description |
|---|---|---|
question_id |
string | Unique question identifier |
subject |
string | Academic subject name (in Tajik) |
category |
string | Knowledge domain category (one of 9 categories) |
question_text |
string | The question text (in Tajik) |
option_a |
string | Answer option A |
option_b |
string | Answer option B |
option_c |
string | Answer option C |
option_d |
string | Answer option D |
correct_answer |
string | The correct answer text |
correct_option |
string | Position of correct answer (option_a, option_b, option_c, or option_d) |
Example Record
| Field | Value |
|---|---|
question_id |
1 |
subject |
Адабиёт (Literature) |
category |
Humanities |
question_text |
Образҳои "Шоҳнома"-ро вобаста ба махсусияташон мувофиқа кунед. |
option_a |
Рустам — Ватандуст |
option_b |
Судоба — Манфӣ |
option_c |
Сиёвуш — Мусбат |
option_d |
Сӯҳроб — Магрур |
correct_answer |
depends on the specific matching |
correct_option |
e.g., option_c |
Note: Each question has exactly one correct answer option.
Knowledge Categories
| Category | Questions | Percentage |
|---|---|---|
| Humanities | 6,087 | 33.8% |
| Other | 4,045 | 22.5% |
| Natural Sciences | 2,934 | 16.3% |
| Economics & Business | 2,229 | 12.4% |
| Engineering & Technology | 1,883 | 10.5% |
| Sports & Tourism | 477 | 2.6% |
| Medicine & Healthcare | 208 | 1.2% |
| Agriculture | 113 | 0.6% |
| Military Science | 40 | 0.2% |
Dataset Creation
Curation Rationale
Tajik, a low-resource language of the Persian family, lacks large-scale benchmarks for knowledge-intensive tasks. TajikMCQA was created to contribute to filling this gap by providing a high-quality MCQA dataset that can support model training and evaluation in Tajik.
Source Data
Data Collection and Processing
The dataset was collected by the authors during their work at the Tajik National University from 2012 to 2016, and subsequently expanded through collaborations with colleagues from the following institutions:
- Tajik National University
- Tajik State Pedagogical University named after Sadriddin Aini
- Bokhtar State University named after Nosir Khusrav
- Other higher education institutions of Tajikistan
The collection process continued over the period 2012–2026. Questions were compiled from various academic sources, examination materials, and educational resources in the Tajik language. Data processing included:
- Filtering out duplicates and low-quality questions.
- Standardizing the format (four options, one correct answer).
- Assigning each question to a subject and a high-level knowledge category.
- Computing basic statistics for analysis.
No automated translation was used; all questions are originally in Tajik.
Who are the source data producers?
The source data producers are educators, lecturers, and content creators from the Tajik universities listed above. The questions reflect the curricula and examination standards of Tajik higher education institutions during the collection period.
Annotations
Annotation process
Annotations (correct answers) were provided by the same educators who authored or curated the questions. No separate annotation campaign was conducted.
Who are the annotators?
The annotators are the same individuals who created the questions — subject matter experts from Tajik universities.
Personal and Sensitive Information
The dataset consists of general knowledge and educational questions. It does not contain personal data, addresses, names, or any information that could be used to identify individuals. No anonymization was necessary.
Bias, Risks, and Limitations
- Over‑representation of certain subjects or domains (e.g., Humanities).
- Under‑representation of rapidly evolving fields.
- Possible factual inaccuracies or outdated information due to the long collection period.
- Limited to the Tajik language; may not generalize to other Persian dialects.
Recommendations
- Be aware of the domain distribution when evaluating models.
- Avoid using the dataset for high-stakes decisions without additional validation.
- Respect the copyright of individual question texts (see Licensing & Legal Notice).
- Consider combining with other resources (e.g., TajikMMLU) for a more comprehensive evaluation.
Citation
BibTeX (dataset):
@misc{tajikmcqa2026,
author = {TajikNLPWorld},
title = {TajikMCQA: A Tajik Multiple Choice Question Answering Dataset},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/TajikNLPWorld/TajikMCQA}
}
APA (dataset): TajikNLPWorld. (2026). TajikMCQA: A Tajik Multiple Choice Question Answering Dataset [Data set]. Hugging Face. https://huggingface.co/datasets/TajikNLPWorld/TajikMCQA
Glossary
- MCQA – Multiple Choice Question Answering: a task where a model selects the correct answer from several options.
- Low-resource language – a language with limited digital resources for NLP.
More Information
For additional details, updates, or to report issues, please visit the Hugging Face dataset repository.
Dataset Card Authors
- TajikNLPWorld (community)
Dataset Card Contact
For questions, takedown requests, or collaboration, please open an issue on the Hugging Face repository:
https://huggingface.co/datasets/TajikNLPWorld/TajikMCQA/discussions
📧 Direct email: cool.araby@gmail.com
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