Triple
T37480225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rec. 709 |
E931392
|
entity |
| Predicate | nominalLumaCoefficientY |
P99570
|
FINISHED |
| Object | 0.2126 |
—
|
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: 0.2126 | Statement: [Rec. 709, nominalLumaCoefficientY, 0.2126]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nominalLumaCoefficientY Context triple: [Rec. 709, nominalLumaCoefficientY, 0.2126]
-
A.
definesLumaCoefficients
chosen
Indicates that one entity specifies the numerical coefficients used to compute luma (perceived brightness) from color components for another entity.
-
B.
hasChromaticityCoordinateY
Indicates that an entity is associated with a specific Y chromaticity coordinate value in a color space.
-
C.
relativeLuminance
Indicates the measured brightness of one entity relative to a reference or to other entities in the same context.
-
D.
luminanceRange
Indicates the span between the minimum and maximum luminance (brightness) values associated with an entity or visual element.
-
E.
CIE1964uvChromaticity_u
Indicates the u coordinate of an entity’s chromaticity in the CIE 1964 uv 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_69f76ec382248190b47844df596123c6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:17 p.m.