Triple
T7402922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rouge Pur Couture |
E170791
|
entity |
| Predicate | hasShadeRange |
P52512
|
FINISHED |
| Object | multiple shades |
—
|
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: multiple shades | Statement: [Rouge Pur Couture, hasShadeRange, multiple shades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShadeRange Context triple: [Rouge Pur Couture, hasShadeRange, multiple shades]
-
A.
isShadeGrown
Indicates that something (typically a crop or plant) is cultivated under the partial cover of shade rather than in direct, full sunlight.
-
B.
hasColorRange
chosen
Indicates that an entity possesses or is associated with a specific span or set of colors, rather than a single discrete color.
-
C.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
D.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
E.
hasBandRange
Indicates that one entity has an associated range or span of bands (such as frequency or wavelength intervals) defined by the other entity.
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26ea27c8190a55e0e0314b463d8 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0323b2c819098ab72c33e6d8534 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:10 p.m.