Triple
T8521399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Pro 13-inch (M1) |
E201700
|
entity |
| Predicate | pixelDensityPPI |
P41264
|
FINISHED |
| Object | 227 |
—
|
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: 227 | Statement: [MacBook Pro 13-inch (M1), pixelDensityPPI, 227]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pixelDensityPPI Context triple: [MacBook Pro 13-inch (M1), pixelDensityPPI, 227]
-
A.
pixelDensity
chosen
Indicates the number of pixels per unit of length or area used to represent or display a visual element.
-
B.
hasPixelPitch
Indicates the distance between adjacent pixels in a display or image sensor, typically measured from center to center.
-
C.
pixelScale
Indicates the ratio or conversion factor between pixel units and real-world or coordinate-space units in a representation or image.
-
D.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
E.
pixelCount
Indicates the total number of individual pixels that make up a given image or visual element.
- 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.