Triple
T8521400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Pro 13-inch (M1) |
E201700
|
entity |
| Predicate | brightnessNits |
P41265
|
FINISHED |
| Object | 500 |
—
|
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: 500 | Statement: [MacBook Pro 13-inch (M1), brightnessNits, 500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brightnessNits Context triple: [MacBook Pro 13-inch (M1), brightnessNits, 500]
-
A.
surfaceBrightnessClass
Indicates the qualitative classification of how bright an extended object (such as a galaxy) appears per unit area on the sky.
-
B.
maximumBrightness
chosen
Indicates the highest level of brightness that an entity can reach or exhibit.
-
C.
surfaceBrightnessProfile
Indicates the distribution of brightness as a function of position across a surface, typically describing how intensity changes from one region to another.
-
D.
apparentBrightness
Indicates how bright one object appears from the perspective or location of another, regardless of its actual intrinsic luminosity.
-
E.
surfaceBrightness_V_mag_per_arcsec2
Indicates the surface brightness of an object measured in V-band magnitudes per square arcsecond, relating its emitted light to the area it covers 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62a490481908ee0ad4ba9a94682 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:16 p.m.