Triple

T2580956
Position Surface form Disambiguated ID Type / Status
Subject Sir John Parker E57087 entity
Predicate employer P7 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: [Sir John Parker, employer, Airbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airbus
Context triple: [Sir John Parker, employer, 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. Airbus Transport International
    Airbus Transport International is a specialized cargo airline that operates Airbus Beluga aircraft to transport oversized aircraft components and other outsize freight for Airbus and its partners.
  • D. 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.
  • E. Boeing
    Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3c6da888190ba7abfe37d182602 completed March 7, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbb123148190bca17d1b70fe5245 completed March 10, 2026, 6:35 a.m.
Created at: March 6, 2026, 9:49 p.m.