@inproceedings{williams-etal-2019-quantifying,
title = "Quantifying the Semantic Core of Gender Systems",
author = "Williams, Adina and
Blasi, Damian and
Wolf-Sonkin, Lawrence and
Wallach, Hanna and
Cotterell, Ryan",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1577",
doi = "10.18653/v1/D19-1577",
pages = "5734--5739",
abstract = "Many of the world{'}s languages employ grammatical gender on the lexeme. For instance, in Spanish, house {``}casa{''} is feminine, whereas the word for paper {``}papel{''} is masculine. To a speaker of a genderless language, this categorization seems to exist with neither rhyme nor reason. But, is the association of nouns to gender classes truly arbitrary? In this work, we present the first large-scale investigation of the arbitrariness of gender assignment that uses canonical correlation analysis as a method for correlating the gender of inanimate nouns with their lexical semantic meaning. We find that the gender systems of 18 languages exhibit a significant correlation with an externally grounded definition of lexical semantics.",
}
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<abstract>Many of the world’s languages employ grammatical gender on the lexeme. For instance, in Spanish, house “casa” is feminine, whereas the word for paper “papel” is masculine. To a speaker of a genderless language, this categorization seems to exist with neither rhyme nor reason. But, is the association of nouns to gender classes truly arbitrary? In this work, we present the first large-scale investigation of the arbitrariness of gender assignment that uses canonical correlation analysis as a method for correlating the gender of inanimate nouns with their lexical semantic meaning. We find that the gender systems of 18 languages exhibit a significant correlation with an externally grounded definition of lexical semantics.</abstract>
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%0 Conference Proceedings
%T Quantifying the Semantic Core of Gender Systems
%A Williams, Adina
%A Blasi, Damian
%A Wolf-Sonkin, Lawrence
%A Wallach, Hanna
%A Cotterell, Ryan
%Y Inui, Kentaro
%Y Jiang, Jing
%Y Ng, Vincent
%Y Wan, Xiaojun
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F williams-etal-2019-quantifying
%X Many of the world’s languages employ grammatical gender on the lexeme. For instance, in Spanish, house “casa” is feminine, whereas the word for paper “papel” is masculine. To a speaker of a genderless language, this categorization seems to exist with neither rhyme nor reason. But, is the association of nouns to gender classes truly arbitrary? In this work, we present the first large-scale investigation of the arbitrariness of gender assignment that uses canonical correlation analysis as a method for correlating the gender of inanimate nouns with their lexical semantic meaning. We find that the gender systems of 18 languages exhibit a significant correlation with an externally grounded definition of lexical semantics.
%R 10.18653/v1/D19-1577
%U https://aclanthology.org/D19-1577
%U https://doi.org/10.18653/v1/D19-1577
%P 5734-5739
Markdown (Informal)
[Quantifying the Semantic Core of Gender Systems](https://aclanthology.org/D19-1577) (Williams et al., EMNLP-IJCNLP 2019)
ACL
- Adina Williams, Damian Blasi, Lawrence Wolf-Sonkin, Hanna Wallach, and Ryan Cotterell. 2019. Quantifying the Semantic Core of Gender Systems. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 5734–5739, Hong Kong, China. Association for Computational Linguistics.