Triple
T21990398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CIE 1931 XYZ |
E543065
|
entity |
| Predicate | hasChromaticityCoordinates |
P66292
|
FINISHED |
| Object | x |
—
|
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: x | Statement: [CIE 1931 XYZ, hasChromaticityCoordinates, x]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChromaticityCoordinates Context triple: [CIE 1931 XYZ, hasChromaticityCoordinates, x]
-
A.
hasChromaticityCoordinateX
chosen
Indicates that an entity has a specified x-coordinate value in a chromaticity color space.
-
B.
chromaticityCoordinatesStandard
Indicates the standard or reference system used to define the chromaticity coordinates associated with a color measurement or representation.
-
C.
hasChromaticityCoordinateY
Indicates that an entity is associated with a specific Y chromaticity coordinate value in a color space.
-
D.
hasColorModel
Indicates that an entity uses or is associated with a particular color representation model (such as RGB, CMYK, or HSV) for defining its colors.
-
E.
hasTristimulusValuesSpace
Indicates that an entity is associated with or defined within a specific tristimulus color values space (such as an XYZ or RGB color space).
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:05 p.m.