@inproceedings{mahowald-2023-discerning,
title = "A Discerning Several Thousand Judgments: {GPT}-3 Rates the Article + Adjective + Numeral + Noun Construction",
author = "Mahowald, Kyle",
editor = "Vlachos, Andreas and
Augenstein, Isabelle",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.20",
doi = "10.18653/v1/2023.eacl-main.20",
pages = "265--273",
abstract = "Knowledge of syntax includes knowledge of rare, idiosyncratic constructions. LLMs must overcome frequency biases in order to master such constructions. In this study, I prompt GPT-3 to give acceptability judgments on the English-language Article + Adjective + Numeral + Noun construction (e.g., {``}a lovely five days{''}). I validate the prompt using the CoLA corpus of acceptability judgments and then zero in on the AANN construction. I compare GPT- 3{'}s judgments to crowdsourced human judgments on a subset of sentences. GPT-3{'}s judgments are broadly similar to human judgments and generally align with proposed constraints in the literature but, in some cases, GPT-3{'}s judgments and human judgments diverge from the literature and from each other.",
}
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<abstract>Knowledge of syntax includes knowledge of rare, idiosyncratic constructions. LLMs must overcome frequency biases in order to master such constructions. In this study, I prompt GPT-3 to give acceptability judgments on the English-language Article + Adjective + Numeral + Noun construction (e.g., “a lovely five days”). I validate the prompt using the CoLA corpus of acceptability judgments and then zero in on the AANN construction. I compare GPT- 3’s judgments to crowdsourced human judgments on a subset of sentences. GPT-3’s judgments are broadly similar to human judgments and generally align with proposed constraints in the literature but, in some cases, GPT-3’s judgments and human judgments diverge from the literature and from each other.</abstract>
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%0 Conference Proceedings
%T A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction
%A Mahowald, Kyle
%Y Vlachos, Andreas
%Y Augenstein, Isabelle
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F mahowald-2023-discerning
%X Knowledge of syntax includes knowledge of rare, idiosyncratic constructions. LLMs must overcome frequency biases in order to master such constructions. In this study, I prompt GPT-3 to give acceptability judgments on the English-language Article + Adjective + Numeral + Noun construction (e.g., “a lovely five days”). I validate the prompt using the CoLA corpus of acceptability judgments and then zero in on the AANN construction. I compare GPT- 3’s judgments to crowdsourced human judgments on a subset of sentences. GPT-3’s judgments are broadly similar to human judgments and generally align with proposed constraints in the literature but, in some cases, GPT-3’s judgments and human judgments diverge from the literature and from each other.
%R 10.18653/v1/2023.eacl-main.20
%U https://aclanthology.org/2023.eacl-main.20
%U https://doi.org/10.18653/v1/2023.eacl-main.20
%P 265-273
Markdown (Informal)
[A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction](https://aclanthology.org/2023.eacl-main.20) (Mahowald, EACL 2023)
ACL