Triple
T30369904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perceptual Quantizer |
E772519
|
entity |
| Predicate | supportsPeakLuminanceUpTo |
P110343
|
FINISHED |
| Object | 10000 cd/m² |
—
|
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: 10000 cd/m² | Statement: [Perceptual Quantizer, supportsPeakLuminanceUpTo, 10000 cd/m²]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPeakLuminanceUpTo Context triple: [Perceptual Quantizer, supportsPeakLuminanceUpTo, 10000 cd/m²]
-
A.
maximumMasteringDisplayLuminance
chosen
Indicates the highest luminance level that a display is capable of outputting during mastering or calibration.
-
B.
supportsWideColorGamut
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
-
C.
maximumBrightness
Indicates the highest level of brightness that an entity can reach or exhibit.
-
D.
hasBetterColorReproductionThan
Indicates that one entity produces more accurate or higher-quality color representation than another entity.
-
E.
luminescenceCapability
Indicates the ability of an entity to emit light through luminescence.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 7:59 p.m.