Triple
T2663180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 13-inch MacBook Pro (M2, 2022) |
E54771
|
entity |
| Predicate | nativeResolution |
P5732
|
FINISHED |
| Object | 2560×1600 |
—
|
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: 2560×1600 | Statement: [13-inch MacBook Pro (M2, 2022), nativeResolution, 2560×1600]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeResolution Context triple: [13-inch MacBook Pro (M2, 2022), nativeResolution, 2560×1600]
-
A.
mainResolution
Indicates that one resolution is the primary or most important resolution associated with a given context or entity.
-
B.
displayResolution
chosen
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
C.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
D.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
-
E.
hasResolution
Indicates that one entity possesses, specifies, or is associated with a particular level or type of resolution (such as detail, clarity, or granularity) in relation to another entity.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96b9f1c8190a8a9460ca88a9aaf |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.