Triple
T2426664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple A12Z Bionic |
E53543
|
entity |
| Predicate | NeuralEngineUseCases |
P39132
|
FINISHED |
| Object | machine learning acceleration |
—
|
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: machine learning acceleration | Statement: [Apple A12Z Bionic, NeuralEngineUseCases, machine learning acceleration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NeuralEngineUseCases Context triple: [Apple A12Z Bionic, NeuralEngineUseCases, machine learning acceleration]
-
A.
neuralEnginePerformance
Indicates the level or efficiency of processing capability provided by a neural engine in performing AI or machine-learning tasks.
-
B.
integratesNeuralEngine
Indicates that one entity incorporates or embeds a neural processing engine within its overall system or architecture.
-
C.
neuralEngineType
Indicates the specific kind or category of neural processing engine associated with or used by an entity.
-
D.
neuralEngineCores
Indicates the number or configuration of neural engine processing cores associated with a given hardware or system.
-
E.
torchRelayNotableFeature
Indicates a notable characteristic, highlight, or distinctive aspect associated with a torch relay event or segment.
- 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_69ab495c44d48190b7235b23719bc3f6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcc74a5108190a3a9631b0cc1a127 |
completed | March 7, 2026, 6:57 a.m. |
| PD | Predicate disambiguation | batch_69abc5aa1b60819081b87f7985c6cff3 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcc73d2e48190b6ad5f3ee75b74eb |
completed | March 7, 2026, 6:57 a.m. |
Created at: March 6, 2026, 9:42 p.m.