Triple

T475279
Position Surface form Disambiguated ID Type / Status
Subject Airbus A320 family E9047 entity
Predicate manufacturer P490 FINISHED
Object Airbus E6021 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: Airbus | Statement: [Airbus A320 family, manufacturer, Airbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airbus
Context triple: [Airbus A320 family, manufacturer, Airbus]
  • A. Airbus chosen
    Airbus is a major European aerospace corporation known for designing and manufacturing commercial airliners such as the A320, A330, and A380 families.
  • B. Aérospatiale
    Aérospatiale was a major French aerospace manufacturer and state-owned company that played a key role in European aviation and space projects, including as a founding partner of Airbus.
  • C. Boeing
    Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
  • D. Embraer
    Embraer is a Brazilian aerospace company best known globally for designing and manufacturing regional and business jets used by airlines and operators worldwide.
  • E. Airbus Helicopters
    Airbus Helicopters is the Airbus Group’s helicopter manufacturing division, known as one of the world’s leading producers of civil and military rotary-wing aircraft.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f03b5e5081908ee3dba9d19a6871 completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a468010c10819090d325d6c3d6f50c completed March 1, 2026, 4:23 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.