Triple

T1721965
Position Surface form Disambiguated ID Type / Status
Subject Airbus A300 E37411 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 A300, manufacturer, Airbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airbus
Context triple: [Airbus A300, 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. Dassault Aviation
    Dassault Aviation is a French aerospace company renowned for designing and producing military fighter jets and business aircraft, including the Mirage and Rafale families and Falcon business jets.
  • D. Boeing
    Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
  • E. The Safran Company
    The Safran Company is a film and television production company best known for producing major horror franchises such as The Conjuring series.
  • 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_69a8861acab88190bb43cde203429399 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa635703dc8190809260de43b72ea3 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeac88e488190aeb6e7a1063405b7 completed March 8, 2026, 9:31 p.m.
Created at: March 4, 2026, 7:30 p.m.