Triple
T11243727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple A12X Bionic |
E266143
|
entity |
| Predicate | supportsMachineLearningAcceleration |
P41983
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Apple A12X Bionic, supportsMachineLearningAcceleration, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMachineLearningAcceleration Context triple: [Apple A12X Bionic, supportsMachineLearningAcceleration, true]
-
A.
supportsNeuralNetworkAcceleration
chosen
Indicates that one entity provides hardware or software capabilities that enhance the speed or efficiency of neural network computations for another entity.
-
B.
acceleratorType
Indicates the kind or category of accelerator associated with or used by an entity.
-
C.
usesNeuralNetworks
Indicates that one entity employs neural network models or techniques as part of its functioning, processing, or decision-making.
-
D.
supportsInferenceOf
Indicates that one entity provides a logical basis or justification for concluding or deriving another entity.
-
E.
supportsMultiModelServing
Indicates that an entity is capable of serving multiple models concurrently within the same system or environment.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e91b0b808190bc38008bb344d180 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:30 p.m.