Triple
T30428594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac Pro (2019) |
E774098
|
entity |
| Predicate | minCpuCores |
P169422
|
FINISHED |
| Object | 8 |
—
|
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 | Statement: [Mac Pro (2019), minCpuCores, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minCpuCores Context triple: [Mac Pro (2019), minCpuCores, 8]
-
A.
smallCoreCount
Indicates that an entity has a relatively low number of processing cores compared to typical or expected configurations.
-
B.
efficiencyCores
Indicates that the related cores are optimized for energy-efficient, low-power processing rather than maximum performance.
-
C.
cpusPerNode
Indicates the number of CPU units allocated or available on each individual node in a system or cluster.
-
D.
additionalAssistantCoresPerCPU
Indicates the number of extra assistant processing cores that are allocated for each CPU unit.
-
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. chosen
Provenance (4 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_69f22491ba248190b9a4776ca8e42d02 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6866aa9f88190b3e139fb374d6606 |
completed | May 2, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 29, 2026, 8:06 p.m.