Triple
T2108228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook |
E42442
|
entity |
| Predicate | hasSecurityFeature |
P2368
|
FINISHED |
| Object | Touch ID |
E41454
|
NE 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: Touch ID | Statement: [MacBook, hasSecurityFeature, Touch ID]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Touch ID Context triple: [MacBook, hasSecurityFeature, Touch ID]
-
A.
Touch ID
chosen
Touch ID is Apple's fingerprint recognition technology used on devices like the MacBook Pro for secure authentication and payments.
-
B.
Face ID
Face ID is Apple's facial recognition system that securely unlocks devices and authorizes actions like payments and app logins using a 3D scan of the user's face.
-
C.
Thumbprint
"Thumbprint" is a horror novella by Joe Hill that follows a traumatized Iraq War veteran who becomes the target of a menacing and mysterious stalker.
-
D.
Find My iPhone
Find My iPhone is an Apple service that lets users locate, lock, or erase their lost or stolen iOS devices remotely.
-
E.
Apple Watch
The Apple Watch is a smartwatch line that integrates closely with the iPhone to provide fitness tracking, health monitoring, notifications, and app functionality on the wrist.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbae03f308190841f5a419bb821f6 |
completed | March 7, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae306ff3a481909ce3c34edb3ab0e2 |
completed | March 9, 2026, 2:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.