Abstract
Traditional explanations for the presence of ambiguous words in natural language have focused on the cost of added complexity that would accompany unambiguous languages. In these theories, ambiguity arises because it represents the optimal trade-off between the informational benefits from precision and the costs for rich languages. In this paper, we suggest that ambiguity remains an inevitable feature of learning languages even without complexity costs. We show that ambiguous words occur more frequently and will therefore be learned more readily, thus triggering more semantic activations between senses of the ambiguous word. We illustrate this through a game-theoretical example.
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Notes
Wasow, Perfors, and Beaver provide a number of arguments for why this presents a critical problem for the understanding of language (Wasow et al. 2005).
A similar idea appeared in Jäger (2007).
We use \(\Vert s_{ij}\Vert \) to indicate the corresponding state in T represented by one sense of ambiguous signal \(s_i\).
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Acknowledgements
The author would like to thank Prof. Kevin Zollman for his comments on the early version of this manuscript. The author is a JSPS International Research Fellow. This research is supported by Chinese National Fund of Social Science (No. 18CZX064) and Grant-in-Aid for JSPS Fellows (No. 20F20012).
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Tang, L. Ambiguity Advantage Under Meaning Activation. J of Log Lang and Inf 31, 99–112 (2022). https://doi.org/10.1007/s10849-021-09349-4
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DOI: https://doi.org/10.1007/s10849-021-09349-4