Triple
T12983632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schie waterway (as seen in View of Delft) |
E321712
|
entity |
| Predicate | lightingRole |
P30545
|
FINISHED |
| Object | reflects soft daylight |
—
|
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: reflects soft daylight | Statement: [Schie waterway (as seen in View of Delft), lightingRole, reflects soft daylight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingRole Context triple: [Schie waterway (as seen in View of Delft), lightingRole, reflects soft daylight]
-
A.
roleAtIllumination
Indicates that an entity holds or held a specific role or position at the organization Illumination.
-
B.
lightingDesigner
Indicates that an entity is responsible for planning, creating, or supervising the lighting design for a production, event, or environment.
-
C.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
-
D.
lightingRequirement
Indicates the level or type of light that is needed for something to function, grow, or be used properly.
-
E.
lightingCharacteristic
chosen
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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:39 p.m.