Triple

T31112787
Position Surface form Disambiguated ID Type / Status
Subject Frances E792996 entity
Predicate aircraftConfigurationOfDesignatedAircraft P3541 FINISHED
Object twin-engine monoplane LITERAL 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: twin-engine monoplane | Statement: [Frances, aircraftConfigurationOfDesignatedAircraft, twin-engine monoplane]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: aircraftConfigurationOfDesignatedAircraft
Context triple: [Frances, aircraftConfigurationOfDesignatedAircraft, twin-engine monoplane]
  • A. aircraftConfiguration chosen
    Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
  • B. aircraftConfigurationProduced
    Indicates that a specific aircraft configuration has been manufactured or produced.
  • C. aircraftRoleOfDesignatedAircraft
    Indicates that an aircraft has the specified operational role or function as a designated aircraft within a particular context or mission.
  • D. intendedAircraft
    Indicates that an aircraft is the one planned or designated to be used for a particular flight, mission, or operation.
  • E. airframerDesignation
    Indicates the specific model or designation assigned to an aircraft by its manufacturing airframer.
  • F. None of above.

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_69f224cfd5d881908ec6447bc321cd58 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6db1f3ec48190a82e7d893d3c76ba completed May 3, 2026, 5:20 a.m.
PD Predicate disambiguation batch_69f6d82adfa481908a5e196d2e18c73f completed May 3, 2026, 5:07 a.m.
Created at: April 29, 2026, 9:04 p.m.