Triple

T1892402
Position Surface form Disambiguated ID Type / Status
Subject visionOS E41899 entity
Predicate includesFramework P1393 FINISHED
Object ARKit E46914 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: ARKit | Statement: [visionOS, includesFramework, ARKit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ARKit
Context triple: [visionOS, includesFramework, ARKit]
  • A. ARKit framework chosen
    ARKit framework is Apple’s augmented reality development platform that enables iOS apps to blend virtual content with the real world using device cameras and motion sensors.
  • B. RealityKit
    RealityKit is Apple’s high-level 3D rendering and augmented reality framework used to build immersive spatial experiences on platforms like visionOS.
  • C. SceneKit
    SceneKit is a high-level 3D graphics framework from Apple used to build and render interactive 3D scenes and animations across its platforms.
  • D. SpriteKit
    SpriteKit is Apple’s 2D game development framework designed for building high-performance, animated games and interactive content across its platforms.
  • E. Vision Pro
    Vision Pro is Apple’s high-end mixed reality headset that blends augmented and virtual reality experiences using advanced displays, sensors, and custom Apple silicon.
  • 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_69a8864b6de0819098d089f6a1b910a7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1480a6c81909fcf5cce4c42fed4 completed March 7, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeae9e1f4819082afdd3b8e065c01 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:34 p.m.