Triple
T5378555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego Model Railroad Museum |
E113022
|
entity |
| Predicate | hasLayoutScale |
P3868
|
FINISHED |
| Object | HO scale |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: HO scale | Statement: [San Diego Model Railroad Museum, hasLayoutScale, HO scale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayoutScale Context triple: [San Diego Model Railroad Museum, hasLayoutScale, HO scale]
-
A.
hasLayout
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another entity.
-
B.
hasScale
chosen
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
C.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
D.
hasScaleFactorForm
Indicates that one entity is represented as a scaled version or proportional form of another, typically via a specific scale factor.
-
E.
hasRelativeSize
Indicates that one entity’s size is being compared to another entity’s size, expressing a relative rather than absolute magnitude.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd88801b188190b9ac35ed89167fa3 |
completed | March 20, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69bd846172788190969f24bc7503c05e |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:03 p.m.