Triple

T36291833
Position Surface form Disambiguated ID Type / Status
Subject Junkers G 24 E893248 entity
Predicate airlineUse P16896 FINISHED
Object passenger airlines in Europe 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: passenger airlines in Europe | Statement: [Junkers G 24, airlineUse, passenger airlines in Europe]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: airlineUse
Context triple: [Junkers G 24, airlineUse, passenger airlines in Europe]
  • A. airlinesUse chosen
    Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
  • B. airlineContext
    Indicates a relationship, situation, or action that specifically occurs within or is constrained by an airline-related context (such as flights, carriers, or air travel operations).
  • C. airline
    Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
  • D. airlineService
    Indicates that an airline operates transportation services (such as flights) between specified locations or for specified routes.
  • E. airlineServicePattern
    Indicates the characteristic way an airline operates its services, such as the routes, frequencies, and scheduling patterns it follows between locations.
  • 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_69f76e4a61f0819084a2b68dbbb4efc6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba6d06f48190a71b5a2f19e2232f completed May 3, 2026, 9:13 p.m.
PD Predicate disambiguation batch_69f7b9a4aad48190a62e41c5e39339d9 completed May 3, 2026, 9:09 p.m.
Created at: May 3, 2026, 4:09 p.m.