Triple

T22725818
Position Surface form Disambiguated ID Type / Status
Subject CF6-50 E561988 entity
Predicate developer P73 FINISHED
Object General Electric Aviation NE NERFINISHED

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: General Electric Aviation | Statement: [CF6-50, developer, General Electric Aviation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: General Electric Aviation
Context triple: [CF6-50, developer, General Electric Aviation]
  • A. GE Aviation chosen
    GE Aviation is a leading aerospace company that designs and manufactures jet engines and related systems for commercial and military aircraft worldwide.
  • B. Pratt & Whitney
    Pratt & Whitney is a major American aerospace manufacturer best known for designing and producing aircraft engines for commercial, military, and general aviation markets.
  • C. Textron Aviation
    Textron Aviation is a major American aircraft manufacturer known for producing Cessna and Beechcraft airplanes for business, general aviation, and special mission use.
  • D. Boeing
    Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
  • E. Spirit AeroSystems
    Spirit AeroSystems is one of the world’s largest non-OEM designers and manufacturers of aerostructures for commercial and defense aircraft.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2454fc984819088213b58ee87a002 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17929710c81909a895622ee32920e completed April 29, 2026, 3:21 a.m.
Created at: April 17, 2026, 3:20 p.m.