Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languages

Ehsaneddin Asgari, Hinrich Schütze


Abstract
We present SuperPivot, an analysis method for low-resource languages that occur in a superparallel corpus, i.e., in a corpus that contains an order of magnitude more languages than parallel corpora currently in use. We show that SuperPivot performs well for the crosslingual analysis of the linguistic phenomenon of tense. We produce analysis results for more than 1000 languages, conducting – to the best of our knowledge – the largest crosslingual computational study performed to date. We extend existing methodology for leveraging parallel corpora for typological analysis by overcoming a limiting assumption of earlier work: We only require that a linguistic feature is overtly marked in a few of thousands of languages as opposed to requiring that it be marked in all languages under investigation.
Anthology ID:
D17-1011
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Martha Palmer, Rebecca Hwa, Sebastian Riedel
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
113–124
Language:
URL:
https://aclanthology.org/D17-1011
DOI:
10.18653/v1/D17-1011
Bibkey:
Cite (ACL):
Ehsaneddin Asgari and Hinrich Schütze. 2017. Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languages. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 113–124, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languages (Asgari & Schütze, EMNLP 2017)
Copy Citation:
PDF:
https://aclanthology.org/D17-1011.pdf
Attachment:
 D17-1011.Attachment.zip
Video:
 https://aclanthology.org/D17-1011.mp4