Triple
T37480085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BT.2020 |
E931389
|
entity |
| Predicate | hasColorGamut |
P205920
|
FINISHED |
| Object | wide color gamut |
—
|
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: wide color gamut | Statement: [BT.2020, hasColorGamut, wide color gamut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorGamut Context triple: [BT.2020, hasColorGamut, wide color gamut]
-
A.
usesColorGamut
Indicates that one entity employs or operates within the color gamut defined or provided by another entity.
-
B.
hasWiderGamutThan
Indicates that one entity supports or encompasses a broader range or spectrum (e.g., of colors or values) than another entity.
-
C.
supportsWideColorGamut
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
-
D.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
E.
hasBetterColorReproductionThan
Indicates that one entity produces more accurate or higher-quality color representation than another entity.
- 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_69f76ec382248190b47844df596123c6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:17 p.m.