The Negative Concord Mystery: Insights from a Language Model

An important recent development in the field of linguistics is the use of small language models to investigate language acquisition. Following this line of research, we investigate the mysterious appearance of ‘negative concord’ (e.g., I didn’t do nothing) in the speech of children whose environment offers no exposure to patterns of this sort. Drawing on a 10-million-word version of the BabyLM corpus, we show that the preference for negative concord over patterns involving a single negative (e.g., I did nothing) can be traced to a cognitive force known as biuniqueness, whose effects will be examined with the help of data from both natural speech and a language model.

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Published
2025-08-20
DOI
https://doi.org/10.3390/info16080710
Primary Topic
Natural Language Processing Techniques
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article
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article

The Negative Concord Mystery: Insights from a Language Model

Haopeng Zhang, William E. O’Grady, Miseon Lee
Information
Natural Language Processing Techniques
article

The Negative Concord Mystery: Insights from a Language Model

Haopeng Zhang, William E. O’Grady, Miseon Lee
article en

Abstract

An important recent development in the field of linguistics is the use of small language models to investigate language acquisition. Following this line of research, we investigate the mysterious appearance of ‘negative concord’ (e.g., I didn’t do nothing) in the speech of children whose environment offers no exposure to patterns of this sort. Drawing on a 10-million-word version of the BabyLM corpus, we show that the preference for negative concord over patterns involving a single negative (e.g., I did nothing) can be traced to a cognitive force known as biuniqueness, whose effects will be examined with the help of data from both natural speech and a language model.

InformationVol. 16(8)
University of Hawaiʻi at Mānoa (US), Hanyang University (KR)
National Research Foundation, Ministry of Education, National Research Foundation of Korea
Openalex Percentile: Top 89%
Natural Language Processing Techniques
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The Negative Concord Mystery: Insights from a Language Model — Haopeng Zhang, William E. O’Grady, et al. · Information (2025) | TGRS Research Map | TGRS