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--- |
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license: apache-2.0 |
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language: |
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- ind |
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- tha |
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pretty_name: Miracl |
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task_categories: |
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- text-retrieval |
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tags: |
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- text-retrieval |
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--- |
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MIRACL is a multilingual dataset for ad hoc retrieval across 18 languages that collectively encompass over three billion native speakers around the world. This resource is designed to support monolingual retrieval tasks, where the queries and the corpora are in the same language. In total, we have gathered over 726k high-quality relevance judgments for 78k queries over Wikipedia in these languages, where all annotations have been performed by native speakers. MIRACL covers Indonesian and Thai languages. Before using this dataloader, please accept the acknowledgement at https://huggingface.co/datasets/miracl/miracl and use huggingface-cli login for authentication. |
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## Languages |
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ind, tha |
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## Supported Tasks |
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Text Retrieval |
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## Dataset Usage |
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### Using `datasets` library |
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``` |
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from datasets import load_dataset |
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dset = datasets.load_dataset("SEACrowd/miracl", trust_remote_code=True) |
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``` |
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### Using `seacrowd` library |
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```import seacrowd as sc |
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# Load the dataset using the default config |
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dset = sc.load_dataset("miracl", schema="seacrowd") |
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# Check all available subsets (config names) of the dataset |
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print(sc.available_config_names("miracl")) |
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# Load the dataset using a specific config |
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dset = sc.load_dataset_by_config_name(config_name="<config_name>") |
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``` |
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More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use). |
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## Dataset Homepage |
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[https://project-miracl.github.io/](https://project-miracl.github.io/) |
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## Dataset Version |
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Source: 1.0.0. SEACrowd: 2024.06.20. |
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## Dataset License |
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Apache license 2.0 (apache-2.0) |
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## Citation |
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If you are using the **Miracl** dataloader in your work, please cite the following: |
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``` |
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@article{10.1162/tacl_a_00595, |
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title = {{MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages}}, |
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author = {Zhang, Xinyu and Thakur, Nandan and Ogundepo, Odunayo and Kamalloo, Ehsan and Alfonso-Hermelo, David and Li, Xiaoguang and Liu, Qun and Rezagholizadeh, Mehdi and Lin, Jimmy}, |
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year = 2023, |
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month = {09}, |
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journal = {Transactions of the Association for Computational Linguistics}, |
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volume = 11, |
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pages = {1114--1131}, |
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doi = {10.1162/tacl\_a\_00595}, |
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issn = {2307-387X}, |
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url = {https://doi.org/10.1162/tacl\%5Fa\%5F00595}, |
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abstract = {{MIRACL is a multilingual dataset for ad hoc retrieval across 18 languages that collectively encompass over three billion native speakers around the world. This resource is designed to support monolingual retrieval tasks, where the queries and the corpora are in the same language. In total, we have gathered over 726k high-quality relevance judgments for 78k queries over Wikipedia in these languages, where all annotations have been performed by native speakers hired by our team. MIRACL covers languages that are both typologically close as well as distant from 10 language families and 13 sub-families, associated with varying amounts of publicly available resources. Extensive automatic heuristic verification and manual assessments were performed during the annotation process to control data quality. In total, MIRACL represents an investment of around five person-years of human annotator effort. Our goal is to spur research on improving retrieval across a continuum of languages, thus enhancing information access capabilities for diverse populations around the world, particularly those that have traditionally been underserved. MIRACL is available at http://miracl.ai/.}}, |
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eprint = {https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl\_a\_00595/2157340/tacl\_a\_00595.pdf} |
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} |
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@article{lovenia2024seacrowd, |
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title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, |
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author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, |
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year={2024}, |
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eprint={2406.10118}, |
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journal={arXiv preprint arXiv: 2406.10118} |
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} |
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``` |
