Triple
T2646879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2 Pro Mac mini |
E53804
|
entity |
| Predicate | maxStorageCapacity |
P14460
|
FINISHED |
| Object | 8 TB |
—
|
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: 8 TB | Statement: [M2 Pro Mac mini, maxStorageCapacity, 8 TB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxStorageCapacity Context triple: [M2 Pro Mac mini, maxStorageCapacity, 8 TB]
-
A.
maximumCapacity
chosen
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
B.
installedCapacity
Indicates the maximum output or production capability that has been set up or built for a system, facility, or equipment, typically measured under specified conditions.
-
C.
maximumVolumeSize
Indicates the largest allowable size or capacity that a volume can have within a given system or context.
-
D.
dataCapacityDigits
Indicates the number of decimal digits used to represent or specify a data capacity value.
-
E.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd919bf2c81908feb768f3391e985 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.