Triple

T10214088
Position Surface form Disambiguated ID Type / Status
Subject MetalKit E242398 entity
Predicate hasClass P9272 FINISHED
Object MTKViewDelegate
MTKViewDelegate is a MetalKit protocol that defines methods for responding to rendering and view update events in an MTKView.
 E849978 NE FINISHED

How this triple was built (4 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: MTKViewDelegate | Statement: [MetalKit, hasClass, MTKViewDelegate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MTKViewDelegate
Context triple: [MetalKit, hasClass, MTKViewDelegate]
  • A. SKView
    SKView is the SpriteKit-specific view class in Apple’s frameworks that renders and manages SpriteKit scenes within an app’s user interface.
  • B. TVMLKit
    TVMLKit is an Apple framework that lets developers build tvOS apps using TVML templates, JavaScript, and web-like technologies instead of fully native UI code.
  • C. SCNView
    SCNView is a Cocoa view class in Apple’s SceneKit framework that renders and displays 3D scene content with built-in support for camera control, lighting, and animations.
  • D. MTK
    MTK is the vehicle registration code for the Main-Taunus-Kreis district in the German state of Hesse.
  • E. PanelView
    PanelView is Rockwell Automation’s family of industrial operator interface terminals used for monitoring and controlling factory automation systems.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MTKViewDelegate
Triple: [MetalKit, hasClass, MTKViewDelegate]
Generated description
MTKViewDelegate is a MetalKit protocol that defines methods for responding to rendering and view update events in an MTKView.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MTKViewDelegate
Target entity description: MTKViewDelegate is a MetalKit protocol that defines methods for responding to rendering and view update events in an MTKView.
  • A. SKView
    SKView is the SpriteKit-specific view class in Apple’s frameworks that renders and manages SpriteKit scenes within an app’s user interface.
  • B. TVMLKit
    TVMLKit is an Apple framework that lets developers build tvOS apps using TVML templates, JavaScript, and web-like technologies instead of fully native UI code.
  • C. SCNView
    SCNView is a Cocoa view class in Apple’s SceneKit framework that renders and displays 3D scene content with built-in support for camera control, lighting, and animations.
  • D. MTK
    MTK is the vehicle registration code for the Main-Taunus-Kreis district in the German state of Hesse.
  • E. PanelView
    PanelView is Rockwell Automation’s family of industrial operator interface terminals used for monitoring and controlling factory automation systems.
  • F. None of above. chosen

Provenance (5 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa24efc081909714d98943543283 completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d652ea80dc81908bc65ee2ec390467 completed April 8, 2026, 1:06 p.m.
NEDg Description generation batch_69d657818b008190a24170717cff53b9 completed April 8, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69d65835a11c819083d069ab0f644d4c completed April 8, 2026, 1:29 p.m.
Created at: April 6, 2026, 11:04 a.m.