Triple

T1815000
Position Surface form Disambiguated ID Type / Status
Subject Airbus A220 E40416 entity
Predicate developedBy P73 FINISHED
Object Bombardier Aerospace E97324 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: Bombardier Aerospace | Statement: [Airbus A220, developedBy, Bombardier Aerospace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bombardier Aerospace
Context triple: [Airbus A220, developedBy, Bombardier Aerospace]
  • A. Bombardier chosen
    Bombardier is a major Canadian manufacturer of trains and rail equipment widely used by transit agencies around the world.
  • B. de Havilland Aircraft Company
    De Havilland Aircraft Company was a major British aviation manufacturer renowned for designing innovative military and civilian aircraft, including iconic World War II planes.
  • C. Gulfstream Aerospace
    Gulfstream Aerospace is an American manufacturer renowned for its high-performance business jets used by corporate, government, and private clients worldwide.
  • D. Airbus
    Airbus is a major European aerospace corporation known for designing and manufacturing commercial airliners such as the A320, A330, and A380 families.
  • E. Bell Textron
    Bell Textron is a major American aerospace manufacturer best known for designing and producing helicopters and tiltrotor aircraft for both military and commercial use.
  • 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65f4628481909ca8e4c2302752ac completed March 6, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf5de46c8190817f67d692e98803 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.