Triple
T29910483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 15-inch MacBook Air (M2) |
E759666
|
entity |
| Predicate | gpuCoresOptions |
P11227
|
FINISHED |
| Object | 10-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: 10-core GPU | Statement: [15-inch MacBook Air (M2), gpuCoresOptions, 10-core GPU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gpuCoresOptions Context triple: [15-inch MacBook Air (M2), gpuCoresOptions, 10-core GPU]
-
A.
gpuCoreCount
chosen
Indicates the number of processing cores present in a GPU.
-
B.
neuralEngineCores
Indicates the number or configuration of neural engine processing cores associated with a given hardware or system.
-
C.
usesNumberOfGPUs
Indicates that an entity operates with, depends on, or is configured to utilize a specified number of GPUs.
-
D.
gpuType
Indicates the specific kind or model category of GPU associated with an entity.
-
E.
gpuComputePerformance
Indicates the level of processing capability a GPU can deliver for computational tasks, typically measured in operations per unit time.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67759bd888190b1beb2fad6058b4d |
completed | May 2, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:10 p.m.