Triple

T16353425
Position Surface form Disambiguated ID Type / Status
Subject WB Group E397113 entity
Predicate hasSubsidiary P254 FINISHED
Object Flytronic E398122 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: Flytronic | Statement: [WB Group, hasSubsidiary, Flytronic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flytronic
Context triple: [WB Group, hasSubsidiary, Flytronic]
  • A. Flytronic chosen
    Flytronic is a Polish company specializing in advanced unmanned aerial systems and related technologies for defense and security applications.
  • B. Thales Avionics
    Thales Avionics is a division of Thales Group that specializes in designing and manufacturing advanced avionics systems and equipment for civil and military aircraft.
  • C. GEC Avionics
    GEC Avionics was a major British aerospace and defense electronics company known for developing advanced avionics systems for military and civil aircraft.
  • D. Esterline Technologies
    Esterline Technologies is a major aerospace and defense manufacturing company known for producing advanced avionics, sensors, and specialized systems for commercial and military aircraft.
  • E. David Clark Company
    David Clark Company is an American aerospace and safety equipment manufacturer best known for producing pressure suits and other life-support gear for NASA astronauts and high-altitude pilots.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2faccab748190b11e0808e422f2ea completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002db841dc8190bfe8a0d8fca1b309 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.