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        <title>A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction</title>
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    <name type="personal">
        <namePart type="given">Kyle</namePart>
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            <title>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics</title>
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        <name type="personal">
            <namePart type="given">Andreas</namePart>
            <namePart type="family">Vlachos</namePart>
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        <name type="personal">
            <namePart type="given">Isabelle</namePart>
            <namePart type="family">Augenstein</namePart>
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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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    <identifier type="doi">10.18653/v1/2023.eacl-main.20</identifier>
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        <url>https://aclanthology.org/2023.eacl-main.20/</url>
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        <date>2023-05</date>
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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)

• A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction (Mahowald, EACL 2023)

ACL

• Kyle Mahowald. 2023. A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 265–273, Dubrovnik, Croatia. Association for Computational Linguistics.