Triple

T19585379
Position Surface form Disambiguated ID Type / Status
Subject Oracle Machine Learning E490093 entity
Predicate hasComponent P35 FINISHED
Object Oracle Machine Learning AutoML UI — NE NERFINISHED

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: Oracle Machine Learning AutoML UI | Statement: [Oracle Machine Learning, hasComponent, Oracle Machine Learning AutoML UI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oracle Machine Learning AutoML UI
Context triple: [Oracle Machine Learning, hasComponent, Oracle Machine Learning AutoML UI]
  • A. Oracle Machine Learning chosen
    Oracle Machine Learning is a suite of in-database machine learning algorithms and tools from Oracle that enables data scientists and analysts to build, deploy, and manage predictive models directly within Oracle databases.
  • B. Oracle Cloud Infrastructure Data Science
    Oracle Cloud Infrastructure Data Science is a managed cloud platform for building, training, deploying, and managing machine learning models at scale within the Oracle Cloud ecosystem.
  • C. AutoML
    AutoML is a set of machine learning tools and services that automatically build, train, and optimize models with minimal manual coding or expertise.
  • D. Azure Machine Learning
    Azure Machine Learning is a cloud-based service from Microsoft for building, training, deploying, and managing machine learning models at scale on Azure.
  • E. Create ML
    Create ML is Apple's machine learning tool that lets developers easily build and train models directly on macOS using simple, user-friendly interfaces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e640513134819082cf233fa3dcc911 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:42 p.m.