Triple
T2646873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2 Pro Mac mini |
E53804
|
entity |
| Predicate | hasGPU |
P11228
|
FINISHED |
| Object | up to 19‑core GPU |
—
|
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: up to 19‑core GPU | Statement: [M2 Pro Mac mini, hasGPU, up to 19‑core GPU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGPU Context triple: [M2 Pro Mac mini, hasGPU, up to 19‑core GPU]
-
A.
gpuType
chosen
Indicates the specific kind or model category of GPU associated with an entity.
-
B.
hasHardwareCompatibilityWith
Indicates that two hardware components or systems can operate together correctly and reliably without conflicts or incompatibilities.
-
C.
integratesGPU
Indicates that one entity incorporates or embeds a GPU as a functional component within its design or system.
-
D.
hardwareAcceleration
Indicates that an operation or process is executed using specialized hardware resources (such as GPU or dedicated accelerators) rather than relying solely on general-purpose CPU computation.
-
E.
hasCPUCore
Indicates that an entity (typically a computing device or processor) possesses or includes a specific CPU core as one of its components.
- 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.