R0021/2026-03-25/Q008 — Query Definition

Research	R0021 — Prompt engineering definitions
Run	2026-03-25
Query	Q008

Query as Received

How does natural language ambiguity (polysemy, regional variation, grammatical flexibility) compare to formal specification languages in terms of precision? How many definitions does the word "set" have in English?

Query as Clarified

• Subject: Comparison of natural language precision vs. formal specification languages
• Scope: Polysemy as a specific dimension of ambiguity; the word "set" as a case study
• Evidence basis: Linguistic research, OED data, formal language theory

Ambiguities Identified

1. "Precision" could mean lack of ambiguity, lack of error, or lack of variation. This research focuses on ambiguity (one-to-many meaning mappings).
2. "Set" has been overtaken as the most polysemous word in the OED — "run" now holds the record. This is reported as a finding.
3. "Formal specification languages" is broad — includes Z notation, TLA+, VDM, and programming-language type systems.

Sub-Questions

1. How many definitions does "set" have in the OED?
2. How does polysemy in English compare to formal language precision?
3. What does linguistic research say about the prevalence and impact of polysemy?
4. What tools do formal specification languages use to eliminate ambiguity?

Hypotheses

ID	Hypothesis	Description
H1	Natural language is vastly more ambiguous than formal languages	The gap between natural language ambiguity and formal specification precision is enormous and well-documented
H2	The ambiguity gap is overstated	Natural language ambiguity is manageable through context, and formal languages have their own limitations
H3	The gap is real but context-dependent	Natural language is more ambiguous in isolation but context resolves most ambiguity in practice; formal languages trade ambiguity for expressiveness