Triple

T1775233
Position Surface form Disambiguated ID Type / Status
Subject Apple Neural Engine E38961 entity
Predicate programmedVia P31541 FINISHED
Object Core ML API E198712 NE FINISHED

How this triple was built (3 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: Core ML API | Statement: [Apple Neural Engine, programmedVia, Core ML API]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Core ML API
Context triple: [Apple Neural Engine, programmedVia, Core ML API]
  • A. Core ML chosen
    Core ML is Apple’s machine learning framework that enables developers to integrate trained models efficiently into iOS, macOS, watchOS, and tvOS apps for on-device intelligence.
  • B. Swift for TensorFlow
    Swift for TensorFlow is an experimental machine learning platform that integrates TensorFlow directly into the Swift programming language to enable differentiable programming and high-performance model development.
  • C. ML.NET
    ML.NET is an open-source, cross-platform machine learning framework for .NET developers to build and integrate custom ML models into .NET applications.
  • D. PlaidML
    PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
  • E. TensorFlow.js
    TensorFlow.js is a JavaScript library that enables training and running machine learning models directly in the browser and in Node.js using TensorFlow.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: programmedVia
Context triple: [Apple Neural Engine, programmedVia, Core ML API]
  • A. implementedProgram
    Indicates that an entity has created, developed, or put into operation a particular program or software system.
  • B. madeProgram
    Indicates that one entity created, developed, or authored a program (such as software or a coded application).
  • C. program
    Indicates that an entity creates, writes, or develops a computer program or software application.
  • D. componentProgram
    Indicates that one entity is a component or module that forms part of a larger program or software system represented by the other entity.
  • E. hasProgramCode
    Indicates that an entity is associated with a specific program identifier or code used to reference or classify it within a system.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab17e368048190b7b73d156400f772 completed March 6, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69adb5c96694819085f3ccafb141802f completed March 8, 2026, 5:45 p.m.
PD Predicate disambiguation batch_69aa61cd4c1c8190a8dff391f5642bfe completed March 6, 2026, 5:10 a.m.
PDg Predicate description generation batch_69ab17d0a644819087e6ce39d6c60da5 completed March 6, 2026, 6:07 p.m.
Created at: March 4, 2026, 7:31 p.m.