Triple
T31498393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Pro 15-inch (2018) |
E803609
|
entity |
| Predicate | processorCores |
P11223
|
FINISHED |
| Object | 6-core options |
—
|
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: 6-core options | Statement: [MacBook Pro 15-inch (2018), processorCores, 6-core options]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: processorCores Context triple: [MacBook Pro 15-inch (2018), processorCores, 6-core options]
-
A.
coreCountCPU
chosen
Indicates the number of processing cores that a CPU has.
-
B.
gpuCoreCount
Indicates the number of processing cores present in a GPU.
-
C.
smallCoreCount
Indicates that an entity has a relatively low number of processing cores compared to typical or expected configurations.
-
D.
performanceCores
Indicates a relationship where certain cores within a processor are designated as high-performance cores optimized for speed and intensive tasks.
-
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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a1ebc9d8819082794ae663fff63d |
completed | May 3, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69f69fe82e5c81909da9db0a2f3bba6d |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:42 p.m.