Triple
T300080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple M1 |
E6177
|
entity |
| Predicate | integratesNeuralEngine |
P11233
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Apple M1, integratesNeuralEngine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: integratesNeuralEngine Context triple: [Apple M1, integratesNeuralEngine, yes]
-
A.
integrates
Indicates that one entity combines or brings together another entity or set of entities into a unified, functioning whole.
-
B.
executionEngine
Indicates the mechanism or component responsible for carrying out, managing, or running a defined process, task, or set of operations.
-
C.
typeOfIntegration
Indicates the specific kind or category of integration that exists or is applied between systems, components, or processes.
-
D.
executionModel
Indicates how a process, task, or operation is carried out or implemented, specifying the underlying method, strategy, or mechanism of its execution.
-
E.
usesIntervention
Indicates that one entity applies, employs, or relies on a specific intervention (such as a treatment, method, or strategy) in relation to another entity or context.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2af1388190b93235602ace679e |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.