@inproceedings{pimentel-etal-2019-meaning,
title = "Meaning to Form: Measuring Systematicity as Information",
author = "Pimentel, Tiago and
McCarthy, Arya D. and
Blasi, Damian and
Roark, Brian and
Cotterell, Ryan",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1171",
doi = "10.18653/v1/P19-1171",
pages = "1751--1764",
abstract = "A longstanding debate in semiotics centers on the relationship between linguistic signs and their corresponding semantics: is there an arbitrary relationship between a word form and its meaning, or does some systematic phenomenon pervade? For instance, does the character bigram {`}gl{'} have any systematic relationship to the meaning of words like {`}glisten{'}, {`}gleam{'} and {`}glow{'}? In this work, we offer a holistic quantification of the systematicity of the sign using mutual information and recurrent neural networks. We employ these in a data-driven and massively multilingual approach to the question, examining 106 languages. We find a statistically significant reduction in entropy when modeling a word form conditioned on its semantic representation. Encouragingly, we also recover well-attested English examples of systematic affixes. We conclude with the meta-point: Our approximate effect size (measured in bits) is quite small{---}despite some amount of systematicity between form and meaning, an arbitrary relationship and its resulting benefits dominate human language.",
}
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<abstract>A longstanding debate in semiotics centers on the relationship between linguistic signs and their corresponding semantics: is there an arbitrary relationship between a word form and its meaning, or does some systematic phenomenon pervade? For instance, does the character bigram ‘gl’ have any systematic relationship to the meaning of words like ‘glisten’, ‘gleam’ and ‘glow’? In this work, we offer a holistic quantification of the systematicity of the sign using mutual information and recurrent neural networks. We employ these in a data-driven and massively multilingual approach to the question, examining 106 languages. We find a statistically significant reduction in entropy when modeling a word form conditioned on its semantic representation. Encouragingly, we also recover well-attested English examples of systematic affixes. We conclude with the meta-point: Our approximate effect size (measured in bits) is quite small—despite some amount of systematicity between form and meaning, an arbitrary relationship and its resulting benefits dominate human language.</abstract>
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%0 Conference Proceedings
%T Meaning to Form: Measuring Systematicity as Information
%A Pimentel, Tiago
%A McCarthy, Arya D.
%A Blasi, Damian
%A Roark, Brian
%A Cotterell, Ryan
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F pimentel-etal-2019-meaning
%X A longstanding debate in semiotics centers on the relationship between linguistic signs and their corresponding semantics: is there an arbitrary relationship between a word form and its meaning, or does some systematic phenomenon pervade? For instance, does the character bigram ‘gl’ have any systematic relationship to the meaning of words like ‘glisten’, ‘gleam’ and ‘glow’? In this work, we offer a holistic quantification of the systematicity of the sign using mutual information and recurrent neural networks. We employ these in a data-driven and massively multilingual approach to the question, examining 106 languages. We find a statistically significant reduction in entropy when modeling a word form conditioned on its semantic representation. Encouragingly, we also recover well-attested English examples of systematic affixes. We conclude with the meta-point: Our approximate effect size (measured in bits) is quite small—despite some amount of systematicity between form and meaning, an arbitrary relationship and its resulting benefits dominate human language.
%R 10.18653/v1/P19-1171
%U https://aclanthology.org/P19-1171
%U https://doi.org/10.18653/v1/P19-1171
%P 1751-1764
Markdown (Informal)
[Meaning to Form: Measuring Systematicity as Information](https://aclanthology.org/P19-1171) (Pimentel et al., ACL 2019)
ACL
- Tiago Pimentel, Arya D. McCarthy, Damian Blasi, Brian Roark, and Ryan Cotterell. 2019. Meaning to Form: Measuring Systematicity as Information. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1751–1764, Florence, Italy. Association for Computational Linguistics.