Triple
T658089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iBook |
E11691
|
entity |
| Predicate | powerConnectorType |
P1374
|
FINISHED |
| Object | MagSafe predecessor (barrel connector) |
—
|
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: MagSafe predecessor (barrel connector) | Statement: [iBook, powerConnectorType, MagSafe predecessor (barrel connector)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: powerConnectorType Context triple: [iBook, powerConnectorType, MagSafe predecessor (barrel connector)]
-
A.
powerPinCount
Indicates the number of power-related pins associated with an electronic component or connector.
-
B.
connectorType
chosen
Indicates the specific kind or category of connection interface that links two entities.
-
C.
suppliesPowerTo
Indicates that one entity provides electrical or energy power required for the operation or functioning of another entity.
-
D.
dataPinCount
Indicates the number of data pins associated with or used by an entity in a given context.
-
E.
supportsPowerDelivery
Indicates that one entity is capable of providing electrical power to another entity through a compatible interface or connection.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fa55e048190bd9913c6c31772d0 |
completed | March 1, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69a49d121cec81909986c91291bb4ca8 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.