Y’all should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts

Gabriel Stanovsky, Ronen Tamari


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.
Anthology ID:
D19-5549
Volume:
Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | WNUT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
375–380
Language:
URL:
https://www.aclweb.org/anthology/D19-5549
DOI:
10.18653/v1/D19-5549
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PDF:
http://aclanthology.lst.uni-saarland.de/D19-5549.pdf