Triple
T12627222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 14 |
E301545
|
entity |
| Predicate | usModelsSim |
P105978
|
FINISHED |
| Object | eSIM only |
—
|
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: eSIM only | Statement: [iPhone 14, usModelsSim, eSIM only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usModelsSim Context triple: [iPhone 14, usModelsSim, eSIM only]
-
A.
modelOfLife
Indicates that one entity serves as a conceptual or representative model describing the life, lifecycle, or living processes of another entity.
-
B.
simulationMethod
Indicates the technique or approach used to perform or implement a simulation.
-
C.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
D.
simType
Indicates that two entities share the same or a comparable type, category, or classification.
-
E.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b195108190ac25bd95e644ace4 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d96179c7648190a05a13991d62bebb |
completed | April 10, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:14 p.m.