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path: "triviaeus.jsonl"
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# Dataset Card for
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<!-- Motivation for the creation of this dataset. -->
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[More Information Needed]
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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[More Information Needed]
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#### Who are the source data producers?
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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[More Information Needed]
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### Annotations [optional]
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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#### Annotation process
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<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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[More Information Needed]
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#### Who are the annotators?
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<!-- This section describes the people or systems who created the annotations. -->
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[More Information Needed]
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#### Personal and Sensitive Information
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Dataset Card Authors [optional]
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## Dataset Card Contact
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[More Information Needed]
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path: "triviaeus.jsonl"
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---
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# Dataset Card for EusTrivia
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EusTrivia consists of 1,715 trivia questions from multiple online sources. 56.3\% of the questions are elementary level (grades 3-6), while the rest are considered challenging. A significant portion of the questions focus specifically on the Basque Country, its language and culture. Each multiple-choice question contains two, three or four choices (3.84 on average) and a single correct answer. Five areas of knowledge are covered:
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- **Humanities and Natural Sciences** (27.8%): This category encompasses questions about history, geography, biology, ecology and other social and natural sciences.
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- **Leisure and Art** (24.5%): This category includes questions on sports and athletes, performative and plastic arts and artists, architecture, cultural events, and related topics.
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- **Music** (16.0%): Here are grouped all the questions about music and musicians, both classical and contemporary.
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- **Language and Literature** (17.1%): This category is concerned with all kinds of literature productions and writers, as well as metalinguistic questions (e.g., definitions, synonyms, and word usage).
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- **Mathematics and ICT** (14.5%): This category covers mathematical problems and questions about ICT, as well as questions about people known for their contributions to these fields of knowledge.
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- **Curated by:** HiTZ Research Center & IXA Research group (University of the Basque Country UPV/EHU)
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- **Language(s) (NLP):** Basque (eu)
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- 📒 Blog Post: [Latxa: An Open Language Model and Evaluation Suite for Basque](https://www.hitz.eus/en/node/340)
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- 📖 Paper: [Latxa: An Open Language Model and Evaluation Suite for Basque](https://openreview.net/forum?id=mMqOvfqFS9)
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- 💻 Code: [hitz-zentroa/latxa](https://github.com/hitz-zentroa/latxa)
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- 📧 Contact: [hitz@ehu.eus](mailto:hitz@ehu.eus)
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## Example
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Basque Example:
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```txt
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Galdera: Zenbat kilo dauka tona batek?
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A. 10.000 kilo
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B. 1.000.000 kilo
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C. 1.000 kilo
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D. 100 kilo
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Erantzuna: C
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```
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English Translation:
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```txt
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Question: How many kilograms are there in a tonne?
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A. 10,000 kilos
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B. 1,000,000 kilos
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C. 1,000 kilos
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D. 100 kilos
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Answer: C
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```
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## Citation
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```bibtex
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@misc{etxaniz2024latxa,
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title={{L}atxa: An Open Language Model and Evaluation Suite for {B}asque},
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author={Julen Etxaniz and Oscar Sainz and Naiara Perez and Itziar Aldabe and German Rigau and Eneko Agirre and Aitor Ormazabal and Mikel Artetxe and Aitor Soroa},
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year={2024},
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eprint={},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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