Triple
T6183127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greeting to the Sun |
E137990
|
entity |
| Predicate | hasLightingEffect |
P69537
|
FINISHED |
| Object | changing colors |
—
|
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: changing colors | Statement: [Greeting to the Sun, hasLightingEffect, changing colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightingEffect Context triple: [Greeting to the Sun, hasLightingEffect, changing colors]
-
A.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
usesLightingFor
Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
-
C.
hasLightingImprovements
Indicates that an entity has enhancements or upgrades made to its lighting conditions or systems.
-
D.
hasLightingPolicy
Indicates that there is a defined policy or set of rules governing how lighting is used, managed, or controlled for the related entity.
-
E.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
- F. None of above. chosen
Provenance (4 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06100c2b0819097f287e86f63d590 |
completed | March 22, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69c055fa0a808190bda37832e3ac150c |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056c87340819088003f427706ebf8 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:19 p.m.