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        <title>Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar</title>
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        <namePart type="given">Jonathan</namePart>
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            <namePart type="given">Emmanuele</namePart>
            <namePart type="family">Chersoni</namePart>
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        <name type="personal">
            <namePart type="given">Cassandra</namePart>
            <namePart type="family">Jacobs</namePart>
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        <name type="personal">
            <namePart type="given">Alessandro</namePart>
            <namePart type="family">Lenci</namePart>
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        <name type="personal">
            <namePart type="given">Tal</namePart>
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        <name type="personal">
            <namePart type="given">Enrico</namePart>
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    <abstract>A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This paper evaluates competing frequency-based and association-based models across eight languages using a metric derived from the Minimum Description Length paradigm. The experiments show that association-based models produce better generalizations across all languages by a significant margin.</abstract>
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    <identifier type="doi">10.18653/v1/W19-2913</identifier>
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%0 Conference Proceedings
%T Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar
%A Dunn, Jonathan
%Y Chersoni, Emmanuele
%Y Jacobs, Cassandra
%Y Lenci, Alessandro
%Y Linzen, Tal
%Y Prévot, Laurent
%Y Santus, Enrico
%S Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F dunn-2019-frequency
%X A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This paper evaluates competing frequency-based and association-based models across eight languages using a metric derived from the Minimum Description Length paradigm. The experiments show that association-based models produce better generalizations across all languages by a significant margin.
%R 10.18653/v1/W19-2913
%U https://aclanthology.org/W19-2913
%U https://doi.org/10.18653/v1/W19-2913
%P 117-128

Markdown (Informal)

[Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar](https://aclanthology.org/W19-2913) (Dunn, CMCL 2019)

• Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar (Dunn, CMCL 2019)

ACL

• Jonathan Dunn. 2019. Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar. In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, pages 117–128, Minneapolis, Minnesota. Association for Computational Linguistics.