Triple

T10502483
Position Surface form Disambiguated ID Type / Status
Subject Apple AI/ML E247704 entity
Predicate developsTechnologyFor P5334 FINISHED
Object watchOS E20923 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: watchOS | Statement: [Apple AI/ML, developsTechnologyFor, watchOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: watchOS
Context triple: [Apple AI/ML, developsTechnologyFor, watchOS]
  • A. watchOS chosen
    watchOS is Apple’s smartwatch operating system that powers the Apple Watch, providing fitness tracking, notifications, and app functionality tightly integrated with iOS and the Apple ecosystem.
  • B. WatchKit
    WatchKit is Apple’s framework that enables developers to build and manage user interfaces and interactions for apps running on Apple Watch.
  • C. 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.
  • D. Wear OS
    Wear OS is Google’s smartwatch operating system designed to bring Android apps, notifications, and Google services to wearable devices.
  • 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 (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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5099c6a848190bf1d5361e9e61108 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dccec72481909bcfb6a9c5df7ba9 completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:25 p.m.