Triple

T12526337
Position Surface form Disambiguated ID Type / Status
Subject Logic Remote E299449 entity
Predicate platform P1292 FINISHED
Object iPhone E10318 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: iPhone | Statement: [Logic Remote, platform, iPhone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: iPhone
Context triple: [Logic Remote, platform, iPhone]
  • A. iPhone chosen
    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.
  • B. iOS
    iOS is Apple’s mobile operating system that powers iPhones and iPads, known for its integrated ecosystem, security features, and curated App Store.
  • C. Ios
    Ios is a Greek island in the Cyclades known for its picturesque whitewashed villages, sandy beaches, and vibrant nightlife.
  • D. iPad
    The iPad is Apple's line of touchscreen tablet computers that popularized modern tablet computing with its sleek design, intuitive interface, and integration into the broader Apple ecosystem.
  • E. IOS
    IOS is the abbreviation for the International Officer School, a U.S. Air Force education program that trains and develops international military officers.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545d7e6c819080c3a85c18caa1ae completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f655762ae88190ab41e23bbd65c566 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:57 p.m.