Triple
T8861062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Pro (16-inch, 2021) |
E210887
|
entity |
| Predicate | peakBrightnessHDR |
P41265
|
FINISHED |
| Object | 1600 nits |
—
|
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: 1600 nits | Statement: [MacBook Pro (16-inch, 2021), peakBrightnessHDR, 1600 nits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakBrightnessHDR Context triple: [MacBook Pro (16-inch, 2021), peakBrightnessHDR, 1600 nits]
-
A.
maximumBrightness
chosen
Indicates the highest level of brightness that an entity can reach or exhibit.
-
B.
supportsHDRStandard
Indicates that one entity is compatible with and can correctly handle or implement a specified HDR (High Dynamic Range) standard defined by another entity.
-
C.
supportsHDRFormat
Indicates that one entity is capable of handling, displaying, or processing content encoded in a specified High Dynamic Range (HDR) format for another entity.
-
D.
surfaceBrightnessProfile
Indicates the distribution of brightness as a function of position across a surface, typically describing how intensity changes from one region to another.
-
E.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e860888190a8a8702377db949e |
completed | April 1, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69cc5c279ea481908c71756f694b66bf |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:50 p.m.