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Confidently making progress on multilingual modeling requires challenging,trustworthy evaluations. We present TyDi QA---a question answering datasetcovering 11 typologically diverse languages with 204K question-answer pairs.The languages of TyDi QA are diverse with regard to their typology---the set oflinguistic features each language expresses---such that we expect modelsperforming well on this set to generalize across a large number of the world'slanguages. We present a quantitative analysis of the data quality andexample-level qualitative linguistic analyses of observed language phenomenathat would not be found in English-only corpora. To provide a realisticinformation-seeking task and avoid priming effects, questions are written bypeople who want to know the answer, but don't know the answer yet, and the datais collected directly in each language without the use of translation.

TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages