Triple

T5432879
Position Surface form Disambiguated ID Type / Status
Subject SpriteKit E121536 entity
Predicate integratesWith P1075 FINISHED
Object SceneKit E209895 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: SceneKit | Statement: [SpriteKit, integratesWith, SceneKit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SceneKit
Context triple: [SpriteKit, integratesWith, SceneKit]
  • A. SceneKit chosen
    SceneKit is a high-level 3D graphics framework from Apple used to build and render interactive 3D scenes and animations across its platforms.
  • B. SpriteKit
    SpriteKit is Apple’s 2D game development framework designed for building high-performance, animated games and interactive content across its platforms.
  • C. RealityKit
    RealityKit is Apple’s high-level 3D rendering and augmented reality framework used to build immersive spatial experiences on platforms like visionOS.
  • D. ARKit framework
    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.
  • E. Core Animation
    Core Animation is Apple’s high-performance graphics rendering and animation framework used to create smooth, hardware-accelerated visual effects in macOS, iOS, and other Apple platforms.
  • 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_69bd463c65f0819082ee6483ab4b466a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd8840ade481909dae2eecc77d73b8 completed March 20, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ac985e48190ba9610e0563c73ab completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:06 p.m.