Triple
T9030259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMPTE ST 2084 |
E216149
|
entity |
| Predicate | luminanceRange |
P85778
|
FINISHED |
| Object | 0 cd/m² to 10,000 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: 0 cd/m² to 10,000 cd/m² | Statement: [SMPTE ST 2084, luminanceRange, 0 cd/m² to 10,000 cd/m²]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: luminanceRange Context triple: [SMPTE ST 2084, luminanceRange, 0 cd/m² to 10,000 cd/m²]
-
A.
relativeLuminance
Indicates the measured brightness of one entity relative to a reference or to other entities in the same context.
-
B.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
C.
hasColorRange
Indicates that an entity possesses or is associated with a specific span or set of colors, rather than a single discrete color.
-
D.
designLuminosity
Indicates the specified luminosity level or brightness characteristics that something is designed or intended to have.
-
E.
surfaceBrightnessProfile
Indicates the distribution of brightness as a function of position across a surface, typically describing how intensity changes from one region to another.
- F. None of above. chosen
Provenance (4 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a9e0aa881908886f453c51ecd0e |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f6dec4081909379bd57c02a5710 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:08 p.m.