Triple
T21830996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple A9 |
E538993
|
entity |
| Predicate | supportsTouchIDGeneration |
P17643
|
FINISHED |
| Object | second generation Touch ID |
—
|
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: second generation Touch ID | Statement: [Apple A9, supportsTouchIDGeneration, second generation Touch ID]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsTouchIDGeneration Context triple: [Apple A9, supportsTouchIDGeneration, second generation Touch ID]
-
A.
hasFingerprintSensor
chosen
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
-
B.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
C.
includesBiometrics
Indicates that one entity contains, uses, or is associated with biometric data or biometric identifiers of another entity.
-
D.
supportsIdentity
Indicates that one entity upholds, validates, or reinforces the identity, self-concept, or role of another entity.
-
E.
has3DTouch
Indicates that one entity supports or is equipped with 3D Touch (pressure-sensitive touch input) functionality in relation to another entity or context.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f091362d9081909f00ad7a2806d5cb |
completed | April 28, 2026, 10:51 a.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.