Triple

T6448788
Position Surface form Disambiguated ID Type / Status
Subject Wilhelm Böing E139810 entity
Predicate partOf P40 FINISHED
Object Boeing family E3507 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: Boeing family | Statement: [Wilhelm Böing, partOf, Boeing family]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boeing family
Context triple: [Wilhelm Böing, partOf, Boeing family]
  • A. Boeing chosen
    Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
  • B. Boeing 7x7 family
    The Boeing 7x7 family is a series of jet airliners produced by Boeing Commercial Airplanes, encompassing its major commercial passenger aircraft models such as the 707, 727, 737, 747, 757, 767, 777, and 787.
  • C. Spirit AeroSystems
    Spirit AeroSystems is one of the world’s largest non-OEM designers and manufacturers of aerostructures for commercial and defense aircraft.
  • D. Boeing Air Transport
    Boeing Air Transport was an early American airline and a predecessor of United Airlines that operated mail and passenger services in the late 1920s and early 1930s.
  • E. Boeing–Saab
    Boeing–Saab is a transatlantic aerospace partnership between Boeing and Saab formed to design and produce advanced military trainer aircraft and related defense systems.
  • 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_69c008b301948190a35854e5284dc822 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069b1a61c81908610264c098d25b0 completed March 22, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bcfc7388190877ad702ea44802d completed March 27, 2026, 9:20 a.m.
Created at: March 22, 2026, 4:47 p.m.