Triple

T633770
Position Surface form Disambiguated ID Type / Status
Subject Saab AB E15976 entity
Predicate hasSubsidiary P254 FINISHED
Object Saab Aeronautics E15976 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: Saab Aeronautics | Statement: [Saab AB, hasSubsidiary, Saab Aeronautics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saab Aeronautics
Context triple: [Saab AB, hasSubsidiary, Saab Aeronautics]
  • A. Saab AB chosen
    Saab AB is a Swedish aerospace and defense company known for developing military aircraft, advanced defense systems, and security solutions.
  • B. Saab Automobile
    Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
  • C. Saab Kockums
    Saab Kockums is a Swedish shipyard and defense company best known for designing and building advanced submarines and naval vessels.
  • D. MTU Aero Engines
    MTU Aero Engines is a leading German aircraft engine manufacturer specializing in the development, production, and maintenance of military and commercial aero engines.
  • E. Avio Aero
    Avio Aero is an Italian aerospace company specializing in the design, production, and maintenance of aircraft engines and gas turbines for civil and military applications.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ec3b6488190aa0dce216c089a2e completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5778b82e8819083fbbedb9c3e340e completed March 2, 2026, 11:42 a.m.
Created at: March 1, 2026, 7:35 p.m.