Triple
T18181236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spinnaker Tower |
E435287
|
entity |
| Predicate | lightingColorChangeable |
P102812
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Spinnaker Tower, lightingColorChangeable, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingColorChangeable Context triple: [Spinnaker Tower, lightingColorChangeable, true]
-
A.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
-
B.
lightingColorChangesForEvents
chosen
Indicates that the color of lighting is altered in response to specific events or event conditions.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
hasLightingEffect
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
E.
lightingCharacteristic
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffb3bc88190a627be9c444d5c7d |
completed | April 19, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.