Triple

T36104976
Position Surface form Disambiguated ID Type / Status
Subject Lisunov Design Bureau E1044327 entity
Predicate aircraftCategoryWorkedOn P106917 FINISHED
Object transport aircraft 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: transport aircraft | Statement: [Lisunov Design Bureau, aircraftCategoryWorkedOn, transport aircraft]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: aircraftCategoryWorkedOn
Context triple: [Lisunov Design Bureau, aircraftCategoryWorkedOn, transport aircraft]
  • A. worksOnAircraft
    Indicates that an entity performs work, maintenance, operation, or related tasks on an aircraft.
  • B. aircraftCategoryProduced chosen
    Indicates that an entity (such as a manufacturer or organization) has produced aircraft belonging to a specified aircraft category.
  • C. aircraftTypesOperated
    Indicates the types or models of aircraft that an entity (such as an airline or operator) uses or operates.
  • D. aircraftTypesUsedOn
    Indicates the types or models of aircraft that are used on or assigned to a particular route, service, operation, or context.
  • E. appliedToAircraftDesignedBy
    Indicates that something (such as a component, system, or regulation) is applied to an aircraft that was designed by a specified designer or organization.
  • 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_69f76e338e2c8190b7f3bc68bec76349 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b69b333081909cadbed3fcb8ecf5 completed May 3, 2026, 8:56 p.m.
PD Predicate disambiguation batch_69f7b4c2a5f8819094ad4621d7b97e0c completed May 3, 2026, 8:49 p.m.
Created at: May 3, 2026, 4:08 p.m.