Y'all should read this! identifying plurality in second-person personal pronouns in english texts

Gabriel Stanovsky, Ronen Tamari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Distinguishing between singular and plural "you" in English is a challenging task which has potential for downstream applications, such as machine translation or coreference resolution. While formal written English does not distinguish between these cases, other languages (such as Spanish), as well as other dialects of English (via phrases such as "y'all"), do make this distinction. We make use of this to obtain distantly-supervised labels for the task on a large-scale in two domains. Following, we train a model to distinguish between the single/plural 'you', finding that although in-domain training achieves reasonable accuracy (≥ 77%), there is still a lot of room for improvement, especially in the domain-transfer scenario, which proves extremely challenging. Our code and data are publicly available.1.

Original languageAmerican English
Title of host publicationW-NUT@EMNLP 2019 - 5th Workshop on Noisy User-Generated Text, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages375-380
Number of pages6
ISBN (Electronic)9781950737840
StatePublished - 2019
Externally publishedYes
Event5th Workshop on Noisy User-Generated Text, W-NUT@EMNLP 2019 - Hong Kong, China
Duration: 4 Nov 2019 → …

Publication series

NameW-NUT@EMNLP 2019 - 5th Workshop on Noisy User-Generated Text, Proceedings

Conference

Conference5th Workshop on Noisy User-Generated Text, W-NUT@EMNLP 2019
Country/TerritoryChina
CityHong Kong
Period4/11/19 → …

Bibliographical note

Publisher Copyright:
© 2019 Association for Computational Linguistics

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