Triple

T5919805
Position Surface form Disambiguated ID Type / Status
Subject Surveillance Self-Defense E131671 entity
Predicate operatingSystemCoverage P16239 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: [Surveillance Self-Defense, operatingSystemCoverage, iOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: iOS
Context triple: [Surveillance Self-Defense, operatingSystemCoverage, 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c049fdb3e08190a72337ab4f48bc8e completed March 22, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c03a95688190bfd51d7ada1e538f completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 4 p.m.