Triple

T292393
Position Surface form Disambiguated ID Type / Status
Subject Airbus E6021 entity
Predicate originalName P65 FINISHED
Object Airbus Industrie 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 Industrie | Statement: [Airbus, originalName, Airbus Industrie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airbus Industrie
Context triple: [Airbus, originalName, Airbus Industrie]
  • 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. Eurofighter GmbH
    Eurofighter GmbH is a multinational aerospace consortium that designs, develops, and produces the Eurofighter Typhoon multirole combat aircraft.
  • E. Rockwell International
    Rockwell International was a major American manufacturing conglomerate best known in aerospace for building the Space Shuttle orbiters and contributing extensively to U.S. defense and space programs.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e975d2c0819082bbf6a0f3d928af completed Feb. 28, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3b071c6e881908e9ca17bd5dc911e completed March 1, 2026, 3:20 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.