R0021/2026-03-25/Q008 — Assessment¶
BLUF¶
The word "set" has 430 definitions in the OED Second Edition (580 senses including phrasal verbs), though "run" has since taken the record with 645 senses. Polysemy is pervasive in natural language — most content words are polysemous, and more frequent words tend to be more polysemous. This stands in stark contrast to formal specification languages where each term has exactly one meaning. Academic research confirms polysemy is "notoriously difficult to treat both theoretically and empirically." For prompt engineering, this means natural language prompts are inherently ambiguous specification instruments.
Probability¶
Rating: Almost certain (95-99%)
Confidence in assessment: High
Confidence rationale: OED data is verifiable. Polysemy research is peer-reviewed.
Reasoning Chain¶
- "Set" has 430 definitions (OED2) / 580 senses including phrasal verbs [SRC01-E01, Medium reliability, High relevance]
- "Run" now holds the record with 645 senses (OED3, 2011) [SRC01-E01]
- Polysemy is pervasive: most content words are polysemous; frequency correlates with polysemy [SRC02-E01, High reliability, High relevance]
- Formal specification languages assign exactly one meaning per term within scope
- JUDGMENT: The ambiguity gap is quantifiable — approximately 430:1 for a common word. This is not a matter of degree but of kind: natural language is fundamentally ambiguous while formal languages are fundamentally precise.
Evidence Base Summary¶
| Source | Description | Reliability | Relevance | Key Finding |
|---|---|---|---|---|
| SRC01 | OED "set" data | Medium | High | 430 definitions (OED2); 645 for "run" (OED3) |
| SRC02 | Polysemy research | High | High | Pervasive, frequent words more polysemous, "notoriously difficult" |
Collection Synthesis¶
| Dimension | Assessment |
|---|---|
| Evidence quality | Medium-High — OED data via secondary source, polysemy research peer-reviewed |
| Source agreement | High — all sources confirm pervasive natural language ambiguity |
| Source independence | Independent — linguistic data and computational linguistics research |
| Outliers | None |
Gaps¶
| Missing Evidence | Impact on Assessment |
|---|---|
| Direct comparison with specific formal languages (Z, TLA+) | Minor — the 1:many vs 1:1 distinction is well-established |
| LLM behavior with polysemous prompts | Moderate — would quantify impact on prompt engineering |
Researcher Bias Check¶
Declared biases: Researcher argues prompt engineering uses an inherently imprecise tool (natural language). This evidence supports that argument.
Influence assessment: The OED data and polysemy research are independently verifiable. The comparison to formal languages is the researcher's frame.
Cross-References¶
| Entity | ID | File |
|---|---|---|
| Hypotheses | H1, H2, H3 | hypotheses/ |
| Sources | SRC01, SRC02 | sources/ |
| ACH Matrix | — | ach-matrix.md |
| Self-Audit | — | self-audit.md |