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+
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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: Tydiqa
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+ task_categories:
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+ - question-answering
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+ tags:
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+ - question-answering
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+ ---
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+
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+ TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs.
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+ The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language
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+ expresses -- such that we expect models performing well on this set to generalize across a large number of the languages
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+ in the world. It contains language phenomena that would not be found in English-only corpora. To provide a realistic
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+ information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but
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+ don’t know the answer yet, (unlike SQuAD and its descendents) and the data is collected directly in each language
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+ without the use of translation (unlike MLQA and XQuAD).
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+
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+
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+ ## Languages
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+
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+ ind, tha
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+
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+ ## Supported Tasks
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+
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+ Question Answering
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+
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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/tydiqa", 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("tydiqa", schema="seacrowd")
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+ # Check all available subsets (config names) of the dataset
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+ print(sc.available_config_names("tydiqa"))
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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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+
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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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+
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+
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+ ## Dataset Homepage
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+
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+ [https://github.com/google-research-datasets/tydiqa](https://github.com/google-research-datasets/tydiqa)
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+
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+ ## Dataset Version
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+
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+ Source: 1.0.0. SEACrowd: 2024.06.20.
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+
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+ ## Dataset License
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+
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+ Apache license 2.0 (apache-2.0)
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+
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+ ## Citation
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+
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+ If you are using the **Tydiqa** dataloader in your work, please cite the following:
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+ ```
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+ \
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+ @article{clark-etal-2020-tydi,
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+ title = "{T}y{D}i {QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages",
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+ author = "Clark, Jonathan H. and
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+ Choi, Eunsol and
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+ Collins, Michael and
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+ Garrette, Dan and
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+ Kwiatkowski, Tom and
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+ Nikolaev, Vitaly and
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+ Palomaki, Jennimaria",
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+ editor = "Johnson, Mark and
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+ Roark, Brian and
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+ Nenkova, Ani",
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+ journal = "Transactions of the Association for Computational Linguistics",
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+ volume = "8",
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+ year = "2020",
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+ address = "Cambridge, MA",
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+ publisher = "MIT Press",
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+ url = "https://aclanthology.org/2020.tacl-1.30",
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+ doi = "10.1162/tacl_a_00317",
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+ pages = "454--470",
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+ abstract = "Confidently making progress on multilingual modeling requires challenging, trustworthy evaluations.
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+ We present TyDi QA{---}a question answering dataset covering 11 typologically diverse languages with 204K
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+ question-answer pairs. The languages of TyDi QA are diverse with regard to their typology{---}the set of
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+ linguistic features each language expresses{---}such that we expect models performing well on this set to
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+ generalize across a large number of the world{'}s languages. We present a quantitative analysis of the data
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+ quality and example-level qualitative linguistic analyses of observed language phenomena that would not be found
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+ in English-only corpora. To provide a realistic information-seeking task and avoid priming effects, questions are
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+ written by people who want to know the answer, but don{'}t know the answer yet, and the data is collected directly
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+ in each language without the use of translation.",
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+ }
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+
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+ @inproceedings{cahyawijaya-etal-2021-indonlg,
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+ title = "{I}ndo{NLG}: Benchmark and Resources for Evaluating {I}ndonesian Natural Language Generation",
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+ author = "Cahyawijaya, Samuel and
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+ Winata, Genta Indra and
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+ Wilie, Bryan and
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+ Vincentio, Karissa and
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+ Li, Xiaohong and
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+ Kuncoro, Adhiguna and
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+ Ruder, Sebastian and
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+ Lim, Zhi Yuan and
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+ Bahar, Syafri and
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+ Khodra, Masayu and
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+ Purwarianti, Ayu and
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+ Fung, Pascale",
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+ booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
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+ month = nov,
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+ year = "2021",
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+ address = "Online and Punta Cana, Dominican Republic",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2021.emnlp-main.699",
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+ doi = "10.18653/v1/2021.emnlp-main.699",
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+ pages = "8875--8898"
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+ }
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+
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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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+
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+ ```