Chapter 5 Polysemy Burden Assessment

The polysemy burden identified in the SDA Design Standard (2019) serialised figures corpus is documented here as part of the evaluation in Chapter 5. Polysemy — the capacity of a single term to carry multiple distinct meanings — constitutes a structural hazard for automated standards interpretation and compliance verification. Three distinct forms of polysemy are reported. WordNet lexical polysemy concerns general-language sense counts. Dimensional polysemy occurs where the same concept carries different quantitative values across SDA categories. Categorical absence polysemy occurs where entities are specified in some categories but absent from others. The analysis draws on 56 unique canonical entities extracted from 189 figure-based design requirement triples. Source data: polysemy-figures-analysis.json and unified-explorer-data-v1.json (generated 2026-03-24 11:49), archived at publish-thesis/publish-data/appendix-data/ch5-artefact-bundle/data-package/canonical/.

WordNet Lexical Polysemy

Of the 56 canonical entities in the serialised vocabulary, 28 (50.0%) are flagged as polysemous based on WordNet sense counts. The polysemy burden is not uniformly distributed; a small number of entities carry disproportionately high sense counts. The table below lists the top 14 polysemous entities by WordNet sense count.

Table A5-PB.1: Most polysemous entities in the serialised vocabulary (top 14 of 28)

Source: unified-explorer-data-v1.json, entity records where is_polysemous = true, sorted by sense_count descending.

The entity Tap is the clearest illustration of the polysemy problem. WordNet records 20 senses spanning the physical fixture (“water_faucet.n.01”), the action of striking (“rap.n.02”), wire-tapping (“wiretap.n.01”), and tap dancing (“tapdance.v.01”). In the SDA context, only the plumbing fixture sense is relevant, but an automated system without domain-specific disambiguation would need to evaluate all 20 candidates. The compound entity Tap_And_Water_Source inherits the same 20-sense burden, compounded by the compositional ambiguity of the conjunction.

The entity Door presents a different polysemy profile: only 5 WordNet senses, but 28 occurrences across the corpus with 20 distinct surface variants. Referential scope is the primary burden for Door: it variously denotes the physical barrier, the doorway opening, the circulation space, and the attached hardware. The serialisation schema resolves all 20 surface forms to a single canonical entity. Underlying referential polysemy remains a challenge for finer-grained semantic analysis. Overall, the lexical polysemy analysis confirms that 50% of the canonical vocabulary requires domain-specific sense disambiguation before general-purpose NLP tools can be applied reliably. Dimensional polysemy is examined in the next section — the same entity there requires different quantitative values depending on the applicable SDA design category.

Dimensional Polysemy

Dimensional polysemy occurs when the same conceptual entity requires different quantitative values depending on the SDA design category. Five cases of dimensional polysemy are identified in the figure-based corpus.

Table A5-PB.2: Dimensional polysemy cases by entity and SDA category

Source: polysemy-figures-analysis.json, dimensional_polysemy array. IL = Improved Liveability; Robust; FA = Fully Accessible; HPS = High Physical Support.

These 5 cases are structurally significant because they represent requirements where the same entity in the same spatial context carries materially different dimensional specifications. Graduated dimensional polysemy is illustrated by the entity Door. Improved Liveability and Robust categories require 820 mm minimum clear opening; Fully Accessible requires 900 mm; High Physical Support requires 950 mm. The 130 mm range is substantive — it determines whether a wheelchair passes with one-sided or two-sided clearance. A compliance system must resolve the applicable category before evaluating the dimensional requirement. Failure to do so produces systematic over-specification or under-specification errors.

A structural asymmetry is also confirmed by the dimensional polysemy cases. Improved Liveability and Robust share identical dimensional values; so do Fully Accessible and High Physical Support. This pairing pattern is confirmed independently by the deontic force distribution in Appendix: Chapter 5 Predicate Coverage and Deontic Force. It suggests the four-category SDA classification effectively operates as a two-tier system at the quantitative level. In summary, the five cases require that any compliance system resolve category context before evaluating dimensional conformance. Categorical absence polysemy is examined next — entities there appear in some categories but are entirely absent from others.

Categorical Absence Polysemy

Categorical absence polysemy occurs when an entity is specified in some SDA categories but absent from others. The analysis identifies 36 such cases. Thirty-four of 36 absence cases follow a single pattern: entities appear in Fully Accessible and High Physical Support but are absent from Improved Liveability and Robust.

Three bathroom entities are absent from lower-tier categories: WC_Pan, Hand_Wash_Basin, and Shower. Spatial clearance entities include Knee_And_Toe_Clearance_Zone and Encroachment-Free_Zone. Kitchen specifications — Cooktop, Kitchen_Bench, Pantry, and Drawer-Style_Dishwasher — are absent from lower-tier categories. Bedroom specifications (Bed, Bedroom) are likewise absent from Improved Liveability and Robust requirements. These absences reflect the SDA framework’s graduated approach to physical support prescription.

Washing_Machine displays the inverse pattern: present in Improved Liveability and Robust, absent from Fully Accessible and High Physical Support. Higher-support categories prescribe alternative laundry configurations in its place. Minimum_900_Mm_Wide_Continuous_Accessible_Path is exclusive to High Physical Support, absent from all three other categories.

Conditional polysemy is recorded in one additional case. WC_Pan in the context of “DIM +/- DIM from the rear wall” carries identical values (800 mm +/- 10 mm) for both FA/HPS and an unspecified category. Polysemy is present but produces no divergent requirements in this degenerate case. Overall, the 36 absence cases define each SDA category’s regulatory reach. Automated systems must represent absence explicitly rather than treating it as a missing value.

Aggregate Polysemy Burden and Implications

Forty-two polysemy cases are identified across all three forms: 5 dimensional, 1 conditional, and 36 categorical absence. The affected corpus contains 189 design requirement triples. A polysemy incidence rate of 22.2% results — approximately one in five requirements is subject to context-dependent semantic variation.

Domain-specific sense disambiguation is required for the 28 lexically polysemous entities (50.0% of the vocabulary) before WordNet-based or embedding-based analysis can be applied reliably. The serialisation schema addresses this through canonical entity resolution, but downstream systems must recognise that general-purpose NLP tools will systematically over-count semantic complexity.

Category context resolution is required by the 5 dimensional polysemy cases before any automated compliance check evaluates dimensional conformance. The 36 categorical absence cases define each category’s regulatory boundaries. Automated systems must distinguish “this entity is not required” from “this entity was not found.” The serialisation schema records which categories each entity’s requirements apply to, making the distinction explicit. Taken together, the three polysemy forms confirm that polysemy is a structural feature of the SDA standard. The schema must represent it explicitly. This polysemy burden evidence supports the artefact design decisions in Chapter 5.