Triple
T15008001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Red Vineyard |
E377757
|
entity |
| Predicate | lightingDepicted |
P30545
|
FINISHED |
| Object | glowing sunset light |
—
|
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: glowing sunset light | Statement: [The Red Vineyard, lightingDepicted, glowing sunset light]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingDepicted Context triple: [The Red Vineyard, lightingDepicted, glowing sunset light]
-
A.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
-
C.
lightType
Indicates the specific category or kind of light associated with an entity or lighting setup.
-
D.
lightingRecommended
Indicates that a particular lighting setup or condition is advised as suitable or optimal for a given context or use.
-
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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:55 a.m.