Triple

T35017181
Position Surface form Disambiguated ID Type / Status
Subject Aero Vodochody E1010083 entity
Predicate L-39AlbatrosRole P53999 FINISHED
Object jet trainer 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: jet trainer | Statement: [Aero Vodochody, L-39AlbatrosRole, jet trainer]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: L-39AlbatrosRole
Context triple: [Aero Vodochody, L-39AlbatrosRole, jet trainer]
  • A. aircraftRoleDesignedFor
    Indicates that an aircraft is specifically designed or intended to perform a particular role or function.
  • B. aircraftTrainedOn
    Indicates that an aircraft has been used as the platform or subject for training a person or crew in its operation or related skills.
  • C. notableAircraftRole chosen
    Indicates that an aircraft is notably associated with performing a particular role or function.
  • D. aircraftRoleOperated
    Indicates that an entity operates or has operated in a specified role or function within the context of aircraft operations.
  • E. basedAircraftRole
    Indicates that an aircraft is regularly stationed at a particular location in a specified operational role or function.
  • 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_69f76dcc3ac8819096a3ed52f5fa2523 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7858aa5508190a07dde993b3356fc completed May 3, 2026, 5:27 p.m.
PD Predicate disambiguation batch_69f7841812f081909d878955d114088e completed May 3, 2026, 5:21 p.m.
Created at: May 3, 2026, 4:01 p.m.