NAACL 2021long20 citations
GPT Perdetry Test: Generating new meanings for new words
Nikolay Malkin, Sameera Lanka, Pranav Goel, Sudha Rao, Nebojsa Jojic
Abstract
Human innovation in language, such as inventing new words, is a challenge for pretrained language models. We assess the ability of one large model, GPT-3, to process new words and decide on their meaning. We create a set of nonce words and prompt GPT-3 to generate their dictionary definitions. We find GPT-3 produces plausible definitions that align with human judgments. Moreover, GPT-3’s definitions are sometimes preferred to those invented by humans, signaling its intriguing ability not just to adapt, but to add to the evolving vocabulary of the English language.
BibTeX
@inproceedings{malkin-etal-2021-gpt,
title = "{GPT} Perdetry Test: Generating new meanings for new words",
author = "Malkin, Nikolay and
Lanka, Sameera and
Goel, Pranav and
Rao, Sudha and
Jojic, Nebojsa",
editor = "Toutanova, Kristina and
Rumshisky, Anna and
Zettlemoyer, Luke and
Hakkani-Tur, Dilek and
Beltagy, Iz and
Bethard, Steven and
Cotterell, Ryan and
Chakraborty, Tanmoy and
Zhou, Yichao",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-main.439/",
doi = "10.18653/v1/2021.naacl-main.439",
pages = "5542--5553"
}