Triple

T9027793
Position Surface form Disambiguated ID Type / Status
Subject App Clips E216090 entity
Predicate partOf P40 FINISHED
Object iOS E8266 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: iOS | Statement: [App Clips, partOf, iOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: iOS
Context triple: [App Clips, partOf, iOS]
  • A. iOS chosen
    iOS is Apple’s mobile operating system that powers iPhones and iPads, known for its integrated ecosystem, security features, and curated App Store.
  • B. IOS
    IOS is the abbreviation for the International Officer School, a U.S. Air Force education program that trains and develops international military officers.
  • C. Ios
    Ios is a Greek island in the Cyclades known for its picturesque whitewashed villages, sandy beaches, and vibrant nightlife.
  • D. iPhone
    The iPhone is Apple's flagship smartphone line that revolutionized mobile technology by combining a touchscreen interface, internet connectivity, and a robust app ecosystem into a single device.
  • E. iPadOS
    iPadOS is Apple’s tablet-focused operating system that builds on iOS with features and interfaces optimized for the iPad’s larger display and multitasking capabilities.
  • 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_69ca83a5fa88819088144801b4dd7245 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6a7fcb308190af90d6be8700e498 completed April 1, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffda9697c81908a1a9e447519ce05 completed April 3, 2026, 5:49 p.m.
Created at: March 30, 2026, 7:07 p.m.