Algorithms in the historical emergence of word senses

Proceedings of the National Academy of Sciences of the United States of America
Christian RamiroYang Xu

Abstract

Human language relies on a finite lexicon to express a potentially infinite set of ideas. A key result of this tension is that words acquire novel senses over time. However, the cognitive processes that underlie the historical emergence of new word senses are poorly understood. Here, we present a computational framework that formalizes competing views of how new senses of a word might emerge by attaching to existing senses of the word. We test the ability of the models to predict the temporal order in which the senses of individual words have emerged, using an historical lexicon of English spanning the past millennium. Our findings suggest that word senses emerge in predictable ways, following an historical path that reflects cognitive efficiency, predominantly through a process of nearest-neighbor chaining. Our work contributes a formal account of the generative processes that underlie lexical evolution.

References

May 23, 2012·Memory & Cognition·Jennifer M RoddMatthew H Davis
Aug 23, 2017·Cognitive Psychology·Zara Harmon, Vsevolod Kapatsinski

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Citations

Jul 11, 2019·Psychonomic Bulletin & Review·Lilia Rissman, Asifa Majid
Dec 29, 2018·PloS One·Tyler J GrayChristopher M Danforth
May 16, 2019·Cognitive Science·Gregory L Murphy
Aug 12, 2020·Nature Human Behaviour·Bill ThompsonGary Lupyan
Dec 29, 2020·Child Development·Ariel StarrMahesh Srinivasan
May 23, 2020·Cognition·Yang XuMahesh Srinivasan
May 22, 2021·Cognitive Science·Barend BeekhuizenSuzanne Stevenson
Aug 18, 2021·Cognition·Aotao XuYang Xu
May 1, 2019··Pawan GoyalAbhik Jana

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