Triple
T6076296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chichu Art Museum |
E135407
|
entity |
| Predicate | lightingDependsOn |
P68513
|
FINISHED |
| Object | time of day |
—
|
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: time of day | Statement: [Chichu Art Museum, lightingDependsOn, time of day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingDependsOn Context triple: [Chichu Art Museum, lightingDependsOn, time of day]
-
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.
laterLighting
Indicates that one lighting event or condition occurs after another in time.
-
D.
lightingDesigner
Indicates that an entity is responsible for planning, creating, or supervising the lighting design for a production, event, or environment.
-
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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575ec63081908a868a41855acf73 |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:11 p.m.