--- dataset_info: - config_name: en features: - name: id dtype: string - name: type dtype: string - name: body dtype: string - name: ideal_answer sequence: string - name: exact_answer sequence: string - name: snippets sequence: string - name: documents sequence: string - name: triples list: - name: p dtype: string - name: s dtype: string - name: o dtype: string - name: concepts sequence: string splits: - name: train num_bytes: 10827410 num_examples: 2251 - name: test num_bytes: 1709411 num_examples: 500 download_size: 5185124 dataset_size: 12536821 - config_name: es features: - name: id dtype: string - name: type dtype: string - name: body dtype: string - name: ideal_answer sequence: string - name: exact_answer sequence: string - name: snippets sequence: string - name: documents sequence: string - name: triples list: - name: p dtype: string - name: s dtype: string - name: o dtype: string - name: concepts sequence: string splits: - name: train num_bytes: 11694723 num_examples: 2251 - name: test num_bytes: 1808733 num_examples: 500 download_size: 5417329 dataset_size: 13503456 - config_name: fr features: - name: id dtype: string - name: type dtype: string - name: body dtype: string - name: ideal_answer sequence: string - name: exact_answer sequence: string - name: snippets sequence: string - name: documents sequence: string - name: triples list: - name: p dtype: string - name: s dtype: string - name: o dtype: string - name: concepts sequence: string splits: - name: train num_bytes: 11760491 num_examples: 2251 - name: test num_bytes: 1799313 num_examples: 500 download_size: 5402467 dataset_size: 13559804 - config_name: it features: - name: id dtype: string - name: type dtype: string - name: body dtype: string - name: ideal_answer sequence: string - name: exact_answer sequence: string - name: snippets sequence: string - name: documents sequence: string - name: triples list: - name: p dtype: string - name: s dtype: string - name: o dtype: string - name: concepts sequence: string splits: - name: train num_bytes: 11241823 num_examples: 2251 - name: test num_bytes: 1737683 num_examples: 500 download_size: 5320580 dataset_size: 12979506 configs: - config_name: en data_files: - split: train path: en/train-* - split: test path: en/test-* - config_name: es data_files: - split: train path: es/train-* - split: test path: es/test-* - config_name: fr data_files: - split: train path: fr/train-* - split: test path: fr/test-* - config_name: it data_files: - split: train path: it/train-* - split: test path: it/test-* license: apache-2.0 task_categories: - question-answering - summarization language: - en - es - fr - it tags: - biology - medical pretty_name: Multilingual BioASQ-6B ---


Mutilingual BioASQ-6B

We translate the BioASQ-6B English Question Answering dataset to generate parallel French, Italian and Spanish versions using the NLLB200 3B parameter model. For more info read the original task description: [http://bioasq.org/participate/challenges_year_6](http://bioasq.org/participate/challenges_year_6) We translate the `body`, `snippets`, `ideal_answer` and `exact_answer` fields. We have validated the quality of the `ideal_answer` field, however, the `exact_answer` field can contain translation artifacts, as NLLB200 often produces low-quality translations of single-word sentences.

- 📖 Paper: [Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain. In LREC-COLING 2024](https://arxiv.org/abs/2404.07613) - 🌐 Project Website: [https://univ-cotedazur.eu/antidote](https://univ-cotedazur.eu/antidote) - Original Dataset: [http://bioasq.org/participate/challenges_year_6](http://bioasq.org/participate/challenges_year_6) - Funding: CHIST-ERA XAI 2019 call. Antidote (PCI2020-120717-2) funded by MCIN/AEI /10.13039/501100011033 and by European Union NextGenerationEU/PRTR ## Citation ```bibtext @proceedings{garcíaferrero2024medical, title={Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain}, author={Iker García-Ferrero and Rodrigo Agerri and Aitziber Atutxa Salazar and Elena Cabrio and Iker de la Iglesia and Alberto Lavelli and Bernardo Magnini and Benjamin Molinet and Johana Ramirez-Romero and German Rigau and Jose Maria Villa-Gonzalez and Serena Villata and Andrea Zaninello}, year={2024}, booktitle={Proceedings of LREC-COLING} } ```