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the claim

Entropy per word can be calculated precisely using information theory and semantics

the verdict
SUPPORTED
the evidence backs this
Recorded sources
4 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that entropy per word can be calculated precisely using information theory and semantics?

Yes. Recent developments in semantic information theory successfully formalize how entropy can be extended and calculated in relation to word meanings and semantic content.

Verdict: SUPPORTED · 4 sources for, 0 against · Last checked

The analysis

The claim states that entropy per word can be calculated precisely using information theory and semantics. Several retrieved papers (such as [3], [4], [5], and [6]) specifically develop semantic information theories that generalize classical Shannon entropy to quantify semantic information, meaning, and semantic entropy. These sources support the claim directly and there are no papers refuting the possibility of calculating semantic entropy.

Evidence for · 4
On the Theory of Semantic Information and Communication for Logical Inference
2024
Presents a mathematical framework for semantic information and communication that defines semantic entropy and related metrics for logical inference.
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Saz, A. F., Xiong, S., Saidutta, Y. M., & Fekri, F. (2024). On the Theory of Semantic Information and Communication for Logical Inference. doi.org. https://doi.org/10.1109/WCNC65185.2026.11555338

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More for · 3
A Semantic Generalization of Shannon’s Information Theory and Applications
2025
Introduces a semantic generalization of Shannon's information theory, establishing rigorous measures for semantic information and meaning.
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Lu, C. (2025). A Semantic Generalization of Shannon’s Information Theory and Applications. doi.org. https://doi.org/10.3390/e27050461

Beyond Shannon: Semantic Information Theory and Methodology
2026
Synthesizes recent advances into a semantic information theory framework that systematically incorporates semantic entropy and synonymity.
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Zhang, P., Niu, K., Liang, Z., Wang, C., Wu, J., Liu, Y., Xu, W., Ma, N., Xu, X., & Zhang, R. (2026). Beyond Shannon: Semantic Information Theory and Methodology. doi.org. https://doi.org/10.1109/TNSE.2026.3676901

Towards a Semantic Information Theory (Introducing Quantum Corollas)
2022
Proposes an extension to information theory connecting quantum information and entropy as linguistic tools to model semantics.
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Tetlow, P., Garg, D., Chase, L., Mattingley-Scott, M., Bronn, N., Naidoo, K., & Reinert, E. (2022). Towards a Semantic Information Theory (Introducing Quantum Corollas)..

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What does the evidence say?

The claim states that entropy per word can be calculated precisely using information theory and semantics. Several retrieved papers (such as [3], [4], [5], and [6]) specifically develop semantic information theories that generalize classical Shannon entropy to quantify semantic information, meaning, and semantic entropy. These sources support the claim directly and there are no papers refuting the possibility of calculating semantic entropy.

Receipt History
first checked05 Aug 2026
judged → SUPPORTED · 8105 Aug 2026
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