Triple

T2037404
Position Surface form Disambiguated ID Type / Status
Subject USS Roe (DD-418) E44663 entity
Predicate shipClass P3141 FINISHED
Object Sims class E6217 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: Sims class | Statement: [USS Roe (DD-418), shipClass, Sims class]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sims class
Context triple: [USS Roe (DD-418), shipClass, Sims class]
  • A. Sims class chosen
    The Sims class was a group of United States Navy destroyers built just before World War II that served extensively in the Atlantic and Pacific theaters.
  • B. Sis
    Sis was the medieval capital city of the Armenian Kingdom of Cilicia, serving as its political and cultural center.
  • C. SIS
    SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
  • D. Simulator
    Simulator is Apple's iOS and watchOS device emulation tool bundled with Xcode, used by developers to run and test apps on virtual Apple devices.
  • E. Odyssey Sims
    Odyssey Sims is an American professional basketball guard known for her standout collegiate career at Baylor University and subsequent success in the WNBA.
  • 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_69a889159ec481908f9e4472d9f480c7 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb95062c481908058d6da35337680 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1ff38fb881909558e4d715a4d314 completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:39 p.m.