Triple

T17666913
Position Surface form Disambiguated ID Type / Status
Subject Bell 407 E440406 entity
Predicate manufacturer P490 FINISHED
Object Bell Textron 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: Bell Textron | Statement: [Bell 407, manufacturer, Bell Textron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bell Textron
Context triple: [Bell 407, manufacturer, Bell Textron]
  • A. Bell Textron chosen
    Bell Textron is a major American aerospace manufacturer best known for designing and producing helicopters and tiltrotor aircraft for both military and commercial use.
  • B. Textron
    Textron is a diversified American industrial conglomerate best known for its aerospace, defense, and industrial products, including brands like Bell, Cessna, and Beechcraft.
  • 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. Textron Systems
    Textron Systems is a U.S.-based defense and aerospace technology company that develops and manufactures advanced military systems, unmanned platforms, and related solutions.
  • 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46eaaaec8819086977d8a5210c44e completed April 19, 2026, 5:56 a.m.
Created at: April 10, 2026, 9:57 a.m.