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

Jonathan H. Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, Jennimaria Palomaki

Abstract
Confidently making progress on multilingual modeling requires challenging, trustworthy evaluations. We present TyDi QA—a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs. The languages of TyDi QA are diverse with regard to their typology—the set of linguistic features each language expresses—such that we expect models performing well on this set to generalize across a large number of the world’s languages. We present a quantitative analysis of the data quality and example-level qualitative linguistic analyses of observed language phenomena that would not be found in English-only corpora. To provide a realistic information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but don’t know the answer yet, and the data is collected directly in each language without the use of translation.
Anthology ID:
2020.tacl-1.30
Volume:
Transactions of the Association for Computational Linguistics, Volume 8
Month:
Year:
2020
Address:
Cambridge, MA
Editors:
Mark Johnson, Brian Roark, Ani Nenkova
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
454–470
Language:
URL:
https://aclanthology.org/2020.tacl-1.30
DOI:
10.1162/tacl_a_00317
Bibkey:
Cite (ACL):
Jonathan H. Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki. 2020. TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages. Transactions of the Association for Computational Linguistics, 8:454–470.
Cite (Informal):
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages (Clark et al., TACL 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/add_acl24_videos/2020.tacl-1.30.pdf
Code
 google-research-datasets/tydiqa +  additional community code
Data
TyDiQA, TyDiQA-GoldP, CoQA, DuReader, MLQA, Natural Questions, QuAC, SQuAD, Universal Dependencies, XNLI, XQuAD
PDF Search Code