Triple

T2623201
Position Surface form Disambiguated ID Type / Status
Subject Gazpromavia E59055 entity
Predicate callsign P1565 FINISHED
Object GAZPROMAVIA E59055 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: GAZPROMAVIA | Statement: [Gazpromavia, callsign, GAZPROMAVIA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GAZPROMAVIA
Context triple: [Gazpromavia, callsign, GAZPROMAVIA]
  • A. Gazpromavia chosen
    Gazpromavia is a Russian airline owned by the energy company Gazprom, operating passenger and cargo flights as well as corporate and charter services, particularly in support of the oil and gas industry.
  • B. Rosneftegaz
    Rosneftegaz is a Russian state-owned holding company that historically managed the government’s stakes in major oil and gas enterprises, including what became Rosneft.
  • C. Bashneft
    Bashneft is a major Russian oil company involved in the exploration, production, and refining of hydrocarbons.
  • D. Rosneft
    Rosneft is a major Russian state-controlled oil company and one of the world’s largest publicly traded petroleum producers.
  • E. GAZ Group
    GAZ Group is a major Russian automotive manufacturer best known for producing commercial vehicles, trucks, and buses.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8af06fc8190ab48d746b8c8892b completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af909b7d9881908930a98d004998fb completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:50 p.m.