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+ Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering
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+ https://github.com/amazon-science/mintaka
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+ We only took entity-type answers and avoided answers that were only numbers or booleans
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+
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+ ```
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+ @inproceedings{sen-etal-2022-mintaka,
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+ title = "Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering",
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+ author = "Sen, Priyanka and
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+ Aji, Alham Fikri and
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+ Saffari, Amir",
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+ booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
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+ month = oct,
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+ year = "2022",
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+ address = "Gyeongju, Republic of Korea",
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+ publisher = "International Committee on Computational Linguistics",
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+ url = "https://aclanthology.org/2022.coling-1.138",
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+ pages = "1604--1619"
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+ }
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+ ```