Triple

T10502535
Position Surface form Disambiguated ID Type / Status
Subject Apple AI/ML organization E247705 entity
Predicate develops P73 FINISHED
Object Core ML framework E198712 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: Core ML framework | Statement: [Apple AI/ML organization, develops, Core ML framework]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Core ML framework
Context triple: [Apple AI/ML organization, develops, Core ML framework]
  • 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. Apple AI/ML
    Apple AI/ML is Apple’s artificial intelligence and machine learning division, responsible for developing and integrating AI technologies across the company’s products and services.
  • D. 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.
  • E. 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.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5099c6a848190bf1d5361e9e61108 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dccec72481909bcfb6a9c5df7ba9 completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:25 p.m.