Triple
T17568580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craig Federighi |
E427878
|
entity |
| Predicate | worksOn |
P3
|
FINISHED |
| Object | iPadOS |
—
|
NE NERFINISHED |
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: iPadOS | Statement: [Craig Federighi, worksOn, iPadOS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: iPadOS Context triple: [Craig Federighi, worksOn, iPadOS]
-
A.
iPadOS
chosen
iPadOS is Apple’s tablet-focused operating system that builds on iOS with features and interfaces optimized for the iPad’s larger display and multitasking capabilities.
-
B.
tvOS
tvOS is Apple’s operating system designed specifically for its Apple TV digital media players, enabling apps, streaming, and interactive entertainment on the television.
-
C.
iOS
iOS is Apple’s mobile operating system that powers iPhones and iPads, known for its integrated ecosystem, security features, and curated App Store.
-
D.
macOS
macOS is Apple’s proprietary Unix-based operating system known for its graphical user interface, tight integration with Apple hardware and services, and strong emphasis on usability and security.
-
E.
visionOS
visionOS is Apple’s mixed-reality operating system designed for spatial computing on Apple Vision Pro, integrating 3D interfaces, gesture and eye tracking, and immersive app experiences.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4592f29d08190bc3de905d35af849 |
completed | April 19, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.