Triple
T30949409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony α7R V |
E788493
|
entity |
| Predicate | aiProcessingUnit |
P11233
|
FINISHED |
| Object | dedicated AI processing unit |
—
|
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: dedicated AI processing unit | Statement: [Sony α7R V, aiProcessingUnit, dedicated AI processing unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aiProcessingUnit Context triple: [Sony α7R V, aiProcessingUnit, dedicated AI processing unit]
-
A.
AIPTechnology
Indicates a relationship where an artificial intelligence platform or system is based on, utilizes, or is characterized by a specific technology.
-
B.
usesNeuralNetworks
Indicates that one entity employs neural network models or techniques as part of its functioning, processing, or decision-making.
-
C.
integratesNeuralEngine
chosen
Indicates that one entity incorporates or embeds a neural processing engine within its overall system or architecture.
-
D.
imageProcessor
Indicates a relationship where an entity performs operations to analyze, transform, or manipulate images.
-
E.
aiFeatures
Indicates that an entity possesses, supports, or is associated with specific artificial intelligence capabilities or functionalities.
- 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:53 p.m.