Triple

T11352048
Position Surface form Disambiguated ID Type / Status
Subject Apple platforms APIs E268859 entity
Predicate includesFramework P1393 FINISHED
Object TVMLKit E121535 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: TVMLKit | Statement: [Apple platforms APIs, includesFramework, TVMLKit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TVMLKit
Context triple: [Apple platforms APIs, includesFramework, TVMLKit]
  • A. TVMLKit chosen
    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.
  • B. TVML
    TVML is Apple’s XML-based markup language used to define the user interface and layout of tvOS apps built with TVMLKit.
  • C. WML
    WML is the National Rail station code for Wilmslow railway station in Cheshire, England.
  • D. MTKView
    MTKView is a specialized view class in Apple’s MetalKit framework that simplifies displaying and managing Metal-rendered graphics content in macOS and iOS apps.
  • E. TVJS
    TVJS is a JavaScript framework used for building interactive tvOS applications, often in conjunction with TVMLKit for Apple TV user interfaces.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea24489081908fbf47fd2e6d709c completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e543a6e97481909dc77a553b217b4d completed April 19, 2026, 9:05 p.m.
Created at: April 8, 2026, 9:33 p.m.